Sync staging with mainline (#524)

* External CI: rename pipeline to rocprofiler-compute (#463) Signed-off-by: Daniel Su <danielsu@amd.com> * Update webui branding (#459) * Update name and icon for browser tab to rocprofiler-compute. Signed-off-by: xuchen-amd <xuchen@amd.com> * Update name and icon for browser tab to rocprofiler-compute. Signed-off-by: xuchen-amd <xuchen@amd.com> --------- Signed-off-by: xuchen-amd <xuchen@amd.com> * Update branding in documentation (#442) * find/replace Omniperf to ROCm Compute Profiler Signed-off-by: Peter Park <peter.park@amd.com> * update name in Sphinx conf Signed-off-by: Peter Park <peter.park@amd.com> * mv what-is-omniperf.rst -> what-is-rocprof-compute.rst Signed-off-by: Peter Park <peter.park@amd.com> * update Tutorials section Signed-off-by: Peter Park <peter.park@amd.com> * add Omniperf as keyword to Conceptual section for internal search Signed-off-by: Peter Park <peter.park@amd.com> * update Reference section Signed-off-by: Peter Park <peter.park@amd.com> * black fmt conf.py Signed-off-by: Peter Park <peter.park@amd.com> * update profile mode and basic usage subsections Signed-off-by: Peter Park <peter.park@amd.com> * update how to use analyze mode subsection Signed-off-by: Peter Park <peter.park@amd.com> * update install section Signed-off-by: Peter Park <peter.park@amd.com> * fix sphinx warnings Signed-off-by: Peter Park <peter.park@amd.com> * fix cmd line examples in profile/mode.rst Signed-off-by: Peter Park <peter.park@amd.com> * update install decision tree image Signed-off-by: Peter Park <peter.park@amd.com> * fix TOC and index Signed-off-by: Peter Park <peter.park@amd.com> fix weird wording * fix cli text: deriving rocprofiler-compute metrics... Signed-off-by: Peter Park <peter.park@amd.com> * update standalone-gui.rst Signed-off-by: Peter Park <peter.park@amd.com> * restore removed doc updates from #428 Signed-off-by: Peter Park <peter.park@amd.com> * update ref to Omniperf in index.rst Signed-off-by: Peter Park <peter.park@amd.com> * fix grafana connection name to match image Signed-off-by: Peter Park <peter.park@amd.com> * update cmds in tutorials Signed-off-by: Peter Park <peter.park@amd.com> --------- Signed-off-by: Peter Park <peter.park@amd.com> * MI300 roofline enablement in rocprofiler-compute (#470) * MI300 roofline enablement in rocprofiler-compute requirements.txt - running some modules complained about numpy version too new, adding extra requirement that numpy be 1.x pmc_roof_perf.txt - adding TCC_BUBBLE_sum counter to profile soc_gfx940.py soc_gfx941.py soc_gfx942.py - remove console logs reading that roofline is temporarily disabled, uncommenting blocks that check for roofline csv and run roofline post-processing roofline_calc.py - add mi300 to supported soc - add new calculation for hbm_data for MI300 using tcc_bubble_sum, checks if counter > 0 to use - add to a few comments roofline-ubuntu-20_04-mi300-rocm6 - binary for the ubuntu systems to enable mi300 roofline calculations from rocm-amdgpu-bench Note- other distros will get roofline bins to enable mi300, but need to be further tested before putting into branch. Signed-off-by: Carrie Fallows <carrie.fallows@amd.com> * Reformatting roofline_calc.py Signed-off-by: Carrie Fallows <carrie.fallows@amd.com> --------- Signed-off-by: Carrie Fallows <carrie.fallows@amd.com> * Update Python format checker (#471) * Add pre commit hook for Python formatting Signed-off-by: coleramos425 <colramos@amd.com> * Update formatting workflow to run on latest Python and add isort formatter Signed-off-by: coleramos425 <colramos@amd.com> * Fix caught yaml formatting issues * Update pyproject file * Add pre-commit hook instruction to CONTRIBUTING guide * Remove target-version from black pyproject.toml * Fixed formatting errors found with black and isort Signed-off-by: David Galiffi <David.Galiffi@amd.com> * Run hook: Whitespaces, fix end of file spaces --------- Signed-off-by: coleramos425 <colramos@amd.com> Signed-off-by: David Galiffi <David.Galiffi@amd.com> Co-authored-by: David Galiffi <David.Galiffi@amd.com> * Bump cryptography from 43.0.0 to 43.0.1 in /docs/sphinx (#473) Bumps [cryptography](https://github.com/pyca/cryptography) from 43.0.0 to 43.0.1. - [Changelog](https://github.com/pyca/cryptography/blob/main/CHANGELOG.rst) - [Commits](https://github.com/pyca/cryptography/compare/43.0.0...43.0.1) --- updated-dependencies: - dependency-name: cryptography dependency-type: indirect ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * Fix file permission on MI300 roofline binary (#477) Signed-off-by: David Galiffi <David.Galiffi@amd.com> * Removing numpy requirements of <2 (#478) Checks are failing if version too high and no need for lower version Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * Fix crash when loading web UI roofline for gfx942 (#479) * Fix crash when loading web UI roofline for gfx942 * Fix formatting Signed-off-by: benrichard-amd <ben.richard@amd.com> * Make same changs for gfx940, gfx942. Signed-off-by: benrichard-amd <ben.richard@amd.com> * Fix formatting in soc_gfx940 and soc_gfx941. Signed-off-by: benrichard-amd <ben.richard@amd.com> --------- Signed-off-by: benrichard-amd <ben.richard@amd.com> * Rebranding name change patch (#469) * Patch in missed name change for rebranding. Signed-off-by: xuchen-amd <xuchen@amd.com> * Patch in missed name change for rebranding. Signed-off-by: xuchen-amd <xuchen@amd.com> --------- Signed-off-by: xuchen-amd <xuchen@amd.com> * Move dependabot.yml to .github/ and bump rocm-docs-core (#481) * Move dependabot.yml to .github/ * Bump rocm-docs-core to 1.8.5 * Bump rocm-docs-core to 1.9.0 * Fix packaging for upgrading (#486) Specify that "rocprofiler-compute" replaces / obsoletes the "omniperf" package. * Renamed extension path from omniperf to rocprofiler_compute (#487) Signed-off-by: Tim Gu <Tim.Gu@amd.com> * MI300 rhel and sles roofline binaries (#480) * Roofline bins for MI300 on rhel and sles distributions Built from rocm-amdgpu-bench, tested on respective distro systems with MI300 hardware. Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * Minor modifications removing hardcoded variables in roofline files. Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> --------- Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * Modify test_profile_general.py ctest to include MI300 enablement (#498) Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * part 1 to support rocprofv3 (#492) * rocprofv3 support initial commit -Can run rocprofv3 but ultimately fails. rocprofv3 says the counter capacity is exceeded and the output CSV file format is different from v1/v2. * Add rocprofv3 detection so v2 can still be used It's hacky but it'll do for now. * Add code path to convert rocprofv3 JSON output into CSV * Grab correct value for Queue ID * Use _sum suffix to sum TCC counters Previously we were specifying each channel for TCC counters. rocprofv3 does not support specifing each TCC channel, and instead will auto sum given the TCC counter name. The counter name with the _sum suffix is also supported and is also supported in v1 and v2. So we will use the TCC counter name with the _sum suffix. * Fix incorrect counter outputs when using rocprofv3 In the JSON output some counters appear multime times and must be summed to get the correct value. These summed values match the rocprofv3 output in CSV mode and also match the rocprofv2 output. * Remove duplicate Correlation_ID and Wave_Size in output * Handle json output that does not contain any dispatches Omniperf was assuming each JSON output from rocprofv3 would always contain dispatches. This is not the case. For example, in a multi-process workload where one of the processes does not dispatch any kernels. A JSON file will still be output for this process but it will not contain any dispatches. * Code cleanup * Update search path for rocprofv3 results Rocprofv3 was updated to include the hostname in the path where it outputs results. * Handle accumulate counters In v1/v2 rocprof uses the SQ_ACCUM_PREV_HIRES counter for the accumualte counters. v3 does not have this. So we need to define our own counters in counter_defs.yaml. For this we use the counter name + _ACCUM, for example SQ_INSTR_LEVEL_SMEM_ACCUM. To use rocprofv3 you will need to update counter_defs.yaml to include these new counter definitions. * Use correct GPU ID When converting JSON -> CSV we were assigning node_id to GPU_ID. Since the JSON contains non-GPU devices, the node_id for GPUs might not start at 0 as expected. This commit maps the agent ID to the appropriate GPU ID. * Parse scratch memory per work item from JSON * Support rocprofv3 CSV parsing JSON decoding is very slow for large files. Include support for parsing rocprofv3 CSV output and make that the default. CSV/JSON can be toggled via the ROCPROF_OUTPUT_FORMAT environment variable e.g. ROCPROF_OUTPUT_FORMAT=csv or ROCPROF_OUTPUT_FORMAT=json * black format after merge * format isort * change return of rocprof_cmd to try to resolve test's error * hack to pick last part of rocminfo's name * debug log of hacks * Modify test_profile_general.py ctest to include MI300 enablement. Currently failing because of explicitly excluded roofline files for the soc and autofailed asserts for roof-only tests- originally in place because roofline was not enabled on mi300 yet. Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * black and isort formated * corrected line of copyright --------- Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> Co-authored-by: benrichard-amd <ben.richard@amd.com> Co-authored-by: YANG WANG <ywang@ywang-ubuntu.amd.com> Co-authored-by: Carrie Fallows <Carrie.Fallows@amd.com> * fix for crash of timestamp of part 1 for rocprofv3 (#499) * fix the error caused by ignoring the lack of counter csv file from rocprofv3 for timestamp * isort and black formated * quick fix for gfx906 roofline (#505) * Multi node support (#503) * [CTest] Pipeline failures for MI300 (#483) * Propagate new chip_id logic to testing workflow Signed-off-by: coleramos425 <colramos@amd.com> * Add a debug line to tests Signed-off-by: coleramos425 <colramos@amd.com> * Trying to set rocprofv2 generally in CTest module Signed-off-by: coleramos425 <colramos@amd.com> * Remove temp debugging lines from CI Signed-off-by: coleramos425 <colramos@amd.com> * Add roofline entry for MI300 expected files in CI tests Signed-off-by: coleramos425 <colramos@amd.com> * Make num_devices modifier global in scope Signed-off-by: coleramos425 <colramos@amd.com> * Change kernel name in PyTest to confirm rocprofv2 bug Related to https://ontrack-internal.amd.com/browse/SWDEV-503453 Signed-off-by: coleramos425 <colramos@amd.com> --------- Signed-off-by: coleramos425 <colramos@amd.com> * Spatial-multiplexing: part 1 profiling stage (#465) * rocprofv3 support initial commit -Can run rocprofv3 but ultimately fails. rocprofv3 says the counter capacity is exceeded and the output CSV file format is different from v1/v2. * Add rocprofv3 detection so v2 can still be used It's hacky but it'll do for now. * Add code path to convert rocprofv3 JSON output into CSV * Grab correct value for Queue ID * Use _sum suffix to sum TCC counters Previously we were specifying each channel for TCC counters. rocprofv3 does not support specifing each TCC channel, and instead will auto sum given the TCC counter name. The counter name with the _sum suffix is also supported and is also supported in v1 and v2. So we will use the TCC counter name with the _sum suffix. * Fix incorrect counter outputs when using rocprofv3 In the JSON output some counters appear multime times and must be summed to get the correct value. These summed values match the rocprofv3 output in CSV mode and also match the rocprofv2 output. * Remove duplicate Correlation_ID and Wave_Size in output * Handle json output that does not contain any dispatches Omniperf was assuming each JSON output from rocprofv3 would always contain dispatches. This is not the case. For example, in a multi-process workload where one of the processes does not dispatch any kernels. A JSON file will still be output for this process but it will not contain any dispatches. * Code cleanup * Update search path for rocprofv3 results Rocprofv3 was updated to include the hostname in the path where it outputs results. * Handle accumulate counters In v1/v2 rocprof uses the SQ_ACCUM_PREV_HIRES counter for the accumualte counters. v3 does not have this. So we need to define our own counters in counter_defs.yaml. For this we use the counter name + _ACCUM, for example SQ_INSTR_LEVEL_SMEM_ACCUM. To use rocprofv3 you will need to update counter_defs.yaml to include these new counter definitions. * debug code * add logic code for multiplexing * minor fix * more fixes * rocprofv3 support initial commit -Can run rocprofv3 but ultimately fails. rocprofv3 says the counter capacity is exceeded and the output CSV file format is different from v1/v2. * Add rocprofv3 detection so v2 can still be used It's hacky but it'll do for now. * Add code path to convert rocprofv3 JSON output into CSV * Grab correct value for Queue ID * Use _sum suffix to sum TCC counters Previously we were specifying each channel for TCC counters. rocprofv3 does not support specifing each TCC channel, and instead will auto sum given the TCC counter name. The counter name with the _sum suffix is also supported and is also supported in v1 and v2. So we will use the TCC counter name with the _sum suffix. * Fix incorrect counter outputs when using rocprofv3 In the JSON output some counters appear multime times and must be summed to get the correct value. These summed values match the rocprofv3 output in CSV mode and also match the rocprofv2 output. * Remove duplicate Correlation_ID and Wave_Size in output * Handle json output that does not contain any dispatches Omniperf was assuming each JSON output from rocprofv3 would always contain dispatches. This is not the case. For example, in a multi-process workload where one of the processes does not dispatch any kernels. A JSON file will still be output for this process but it will not contain any dispatches. * Code cleanup * Update search path for rocprofv3 results Rocprofv3 was updated to include the hostname in the path where it outputs results. * Handle accumulate counters In v1/v2 rocprof uses the SQ_ACCUM_PREV_HIRES counter for the accumualte counters. v3 does not have this. So we need to define our own counters in counter_defs.yaml. For this we use the counter name + _ACCUM, for example SQ_INSTR_LEVEL_SMEM_ACCUM. To use rocprofv3 you will need to update counter_defs.yaml to include these new counter definitions. * count accu files as well * Use correct GPU ID When converting JSON -> CSV we were assigning node_id to GPU_ID. Since the JSON contains non-GPU devices, the node_id for GPUs might not start at 0 as expected. This commit maps the agent ID to the appropriate GPU ID. * fix error with csv file parse from json and merge during post-processing * implemented parsing of csv files from v3 output for optimization * Parse scratch memory per work item from JSON * Support rocprofv3 CSV parsing JSON decoding is very slow for large files. Include support for parsing rocprofv3 CSV output and make that the default. CSV/JSON can be toggled via the ROCPROF_OUTPUT_FORMAT environment variable e.g. ROCPROF_OUTPUT_FORMAT=csv or ROCPROF_OUTPUT_FORMAT=json * black format after merge * format isort * change return of rocprof_cmd to try to resolve test's error * hack to pick last part of rocminfo's name * debug log of hacks * Modify test_profile_general.py ctest to include MI300 enablement. Currently failing because of explicitly excluded roofline files for the soc and autofailed asserts for roof-only tests- originally in place because roofline was not enabled on mi300 yet. Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * black and isort formated * formated by isort and black * change default rocprof's output to csv * repaired crash caused by missing csv counter file when running for timestamp * change name to spatial-multiplexing from multiplexing * make necessary modification for review * set the value of spatial_multiplexing in argument defautly to None * repair the part that blocks regular pmc files' generation --------- Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> Co-authored-by: benrichard-amd <ben.richard@amd.com> Co-authored-by: fei.zheng <fei.zheng@amd.com> Co-authored-by: YANG WANG <ywang@ywang-ubuntu.amd.com> Co-authored-by: Carrie Fallows <Carrie.Fallows@amd.com> * Simple fix for gpu model value. (#508) Signed-off-by: xuchen-amd <xuchen@amd.com> * Add FP64 to plot adhering to pdf name (#507) * Replacing FP32-only plot with an FP32&FP64 combo plot. Results will likely be negligible but the plot name indicates both should be graphed. Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * Remove duplicate AI plot to clean up fp32 fp64 graph Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> --------- Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * Add gpu series for roofline (#510) * Add gpu_series for roofline. * Use gpu_series in path names for roofline. * Fix TCC on MI200 when introduce rocprofv3 (#509) * quick fix for v2 * one more fix * revert a bit --------- Co-authored-by: ywang103-amd <ywang103@amd.com> * Bump rocm-docs-core from 1.9.0 to 1.12.0 in /docs/sphinx (#511) Bumps [rocm-docs-core](https://github.com/ROCm/rocm-docs-core) from 1.9.0 to 1.12.0. - [Release notes](https://github.com/ROCm/rocm-docs-core/releases) - [Changelog](https://github.com/ROCm/rocm-docs-core/blob/develop/CHANGELOG.md) - [Commits](https://github.com/ROCm/rocm-docs-core/compare/v1.9.0...v1.12.0) --- updated-dependencies: - dependency-name: rocm-docs-core dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * Update sample roofline plot img (#516) * Modify path to use gpu_model instead of gpu_series to match other workload directory path creation/search points. Affects manual testing, does not seem to affect ctests. (#513) Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> * Improve formatting when displaying rocprof command. (#476) * Improve formatting when displaying rocprof command. Signed-off-by: xuchen-amd <xuchen@amd.com> * Fix python formatting. Signed-off-by: xuchen-amd <xuchen@amd.com> * Strip unwanted characters (rocprofv1 specific) from rocprof commands. Signed-off-by: xuchen-amd <xuchen@amd.com> * Strip unwanted characters (rocprofv1 specific) from rocprof commands. Signed-off-by: xuchen-amd <xuchen@amd.com> * Save the unmodified arguments for rocprof for debug message display. Signed-off-by: xuchen-amd <xuchen@amd.com> --------- Signed-off-by: xuchen-amd <xuchen@amd.com> * quick fix for mpi_support (#518) * Pass accumulate counters to rocprofv3 using -E option (#522) rocprofv3 has a new -E option where extra counters can be passed (see accum_counters.yaml) instead of defining them in counter_defs.yaml. * Unify all file handling with pathlib (#512) * Replace occurences of os.path functions with equivalent functions from pathlib library * Remove unwanted imports of os.path and os * Add coding guidelines for using pathlib instead of os.path * Auto sync staging and mainline on a weekly cadence (#517) Signed-off-by: coleramos425 <colramos@amd.com> --------- Signed-off-by: Daniel Su <danielsu@amd.com> Signed-off-by: xuchen-amd <xuchen@amd.com> Signed-off-by: Peter Park <peter.park@amd.com> Signed-off-by: Carrie Fallows <carrie.fallows@amd.com> Signed-off-by: coleramos425 <colramos@amd.com> Signed-off-by: David Galiffi <David.Galiffi@amd.com> Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com> Signed-off-by: benrichard-amd <ben.richard@amd.com> Signed-off-by: Tim Gu <Tim.Gu@amd.com> Co-authored-by: Daniel Su <danielsu@amd.com> Co-authored-by: xuchen-amd <xuchen@amd.com> Co-authored-by: Peter Park <peter.park@amd.com> Co-authored-by: cfallows-amd <Carrie.Fallows@amd.com> Co-authored-by: David Galiffi <David.Galiffi@amd.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Ben Richard <143630488+benrichard-amd@users.noreply.github.com> Co-authored-by: Tim Gu <Tim.Gu@amd.com> Co-authored-by: ywang103-amd <ywang103@amd.com> Co-authored-by: benrichard-amd <ben.richard@amd.com> Co-authored-by: YANG WANG <ywang@ywang-ubuntu.amd.com> Co-authored-by: Fei Zheng <44449748+feizheng10@users.noreply.github.com> Co-authored-by: fei.zheng <fei.zheng@amd.com> Co-authored-by: vedithal-amd <Vignesh.Edithal@amd.com> [ROCm/rocprofiler-compute commit: 272e5b6e32]
2025-01-02 13:29:47 -08:00
@@ -43,4 +43,4 @@ pr:
  drafts: false

 jobs:
-  - template: ${{ variables.CI_COMPONENT_PATH }}/omniperf.yml@pipelines_repo
+  - template: ${{ variables.CI_COMPONENT_PATH }}/rocprofiler-compute.yml@pipelines_repo
@@ -10,4 +10,4 @@ docs/ @ROCm/rocm-documentation
 cmake/ @koomie
 tests/ @koomie
 CMakeLists.txt @koomie
-utils/ @koomie
+utils/ @koomie
@@ -18,7 +18,7 @@ body:
      placeholder: e.g. I found the following error when trying to...
    validations:
      required: true
-  
+
  - type: markdown
    attributes:
      value: |
@@ -128,4 +128,4 @@ body:
    id: context
    attributes:
      label: Additional Context
-      description: Add any other context about the problem here.
+      description: Add any other context about the problem here.
@@ -42,4 +42,4 @@ body:
    id: context
    attributes:
      label: Additional context
-      description: Add any other context or screenshots about the feature request here.
+      description: Add any other context or screenshots about the feature request here.
@@ -20,4 +20,4 @@ body:
    id: context
    attributes:
      label: Additional context
-      description: Add any other context or screenshots about the question here.
+      description: Add any other context or screenshots about the question here.
@@ -60,4 +60,3 @@ jobs:
      - name: Deploy to GitHub Pages
        id: deployment
        uses: actions/deploy-pages@v4
-
@@ -14,25 +14,25 @@ concurrency:
 jobs:
  python:
    runs-on: ubuntu-20.04
-    strategy:
-      matrix:
-        python-version: [3.8, 3.9]

    steps:
    - name: Checkout
      uses: actions/checkout@v4
-    - name: Set up Python ${{ matrix.python-version }}
+    - name: Set up Python '3.x'
      uses: actions/setup-python@v5
      with:
-        python-version: ${{ matrix.python-version }}
+        python-version: '3.x'
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
-        python -m pip install black
+        python -m pip install black isort
        if [ -f requirements.txt ]; then python -m pip install -r requirements.txt; fi
-    - name: black format
-      run: |
-        black --diff --check .
+    - name: Run black formatter
+      uses: psf/black@stable
+      with:
+        use_pyproject: true
+    - name: Run isort formatter
+      uses: isort/isort-action@master

  cmake:
    runs-on: ubuntu-20.04
@@ -30,7 +30,7 @@ jobs:
    runs-on: [mi100, rhel9]

    env:
-       PYTHONPATH: /home1/ciuser/omniperf_deps
+       PYTHONPATH: /home1/ciuser/rocprofiler-compute_deps
       CI_VISIBLE_DEVICES: 1
    name: ROCm v${{ matrix.version }} / ${{ matrix.hardware }} / ${{ matrix.profiler }}
    steps:
@@ -62,4 +62,3 @@ jobs:
          files: |
            build/rocprofiler-compute-${{github.ref_name}}.tar.gz
          name: ${{ env.RELEASE_NAME }}
-
@@ -105,4 +105,3 @@ jobs:
          module load rocprofiler-compute
          module list
          rocprof-compute --version
-
@@ -0,0 +1,27 @@
+name: Sync Mainline with Staging
+on:
+    workflow_dispatch:
+    schedule:
+      - cron: 0 5 * * sun
+
+jobs:
+  promote-stg-to-main:
+    if: github.repository == 'ROCm/rocprofiler-compute'
+    runs-on: ubuntu-latest
+    name: Promote Staging to Mainline
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+            ref: amd-mainline
+            fetch-depth: '0'
+
+      - name: Merge - Fast Forward Only
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          git checkout amd-mainline
+          git checkout -b promote-staging-$(date +%F)
+          git merge --ff-only origin/amd-staging
+          git push -u origin HEAD
+          gh pr create --base amd-mainline --title "Promote \`amd-staging\` to \`amd-mainline\`" --fill --label "automerge"
@@ -23,4 +23,3 @@ VERSION.sha
 # documentation artifacts
 /_build
 _toc.yml
-
@@ -0,0 +1,19 @@
+default_stages: [pre-commit]
+fail_fast: true
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v2.3.0
+    hooks:
+      - id: check-yaml
+      - id: end-of-file-fixer
+      - id: trailing-whitespace
+  # Python import sorting
+  - repo: https://github.com/pycqa/isort
+    rev: 5.12.0
+    hooks:
+      - id: isort
+  # Python formatting (Using this mirror lets us use mypyc-compiled black, which is about 2x faster)
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 24.8.0
+    hooks:
+      - id: black
@@ -1,23 +1,23 @@
 {
    "creators": [
        {
-            "affiliation": "AMD", 
+            "affiliation": "AMD",
            "name": "Xiaomin Lu"
-        }, 	
+        },
        {
-            "affiliation": "AMD Research", 
+            "affiliation": "AMD Research",
            "name": "Cole Ramos"
        },
        {
-            "affiliation": "AMD", 
+            "affiliation": "AMD",
            "name": "Fei Zheng"
        },
        {
-            "affiliation": "AMD Research", 
+            "affiliation": "AMD Research",
            "name": "Karl W. Schulz"
        },
        {
-            "affiliation": "AMD Research", 	    
+            "affiliation": "AMD Research",
            "name": "Jose Santos"
        }
    ]
@@ -21,7 +21,7 @@ Full documentation for ROCm Compute Profiler is available at [https://rocm.docs.

 ### Optimized

-* reduced running time of Omniperf when profiling (#384) 
+* reduced running time of Omniperf when profiling (#384)
 * console logging improvements

 ## Omniperf 2.0.1 for ROCm 6.2.0
@@ -42,7 +42,7 @@ Full documentation for ROCm Compute Profiler is available at [https://rocm.docs.
  * overhauled CI/CD that spans all modes (#179)
  * extensible SoC classes to better support adding new hardware configs (#180)
  * --kernel-verbose no longer overwrites kernel names (#193)
-  * general cleanup and improved organization of source code (#200) (#210) 
+  * general cleanup and improved organization of source code (#200) (#210)
  * separate requirement files for docs and testing dependencies (#205) (#262) (#358)
  * add support for MI300 hardware (#231)
  * upgrade Grafana assets and build script to latest release (#235)
@@ -89,14 +89,14 @@ Full documentation for ROCm Compute Profiler is available at [https://rocm.docs.
  * roofline support for sles15 sp4 and future service packs (#109)
  * adding dockerfiles for all supported Linux distros
  * new examples for `--roof-only` and `--kernel` options added to documentation
-  
+
  * enable cli analysis in Windows (#110)
  * optional random port number in standalone GUI (#111)
  * limit length of visible kernelName in `--kernel-names` option (#115)
  * adjust metric definitions (#117, #130)
  * manually merge rocprof runs, overriding default rocprofiler implementation (#125)
  * fixed compatibility issues with Python 3.11 (#131)
-  
+
 ## Omniperf 1.0.8-PR2 (17 Apr 2023)

  * ux improvements in standalone GUI (#101)
@@ -112,7 +112,7 @@ Full documentation for ROCm Compute Profiler is available at [https://rocm.docs.
  * remove unused python modules (#96)
  * fix empirical roofline calculation for single dispatch workloads (#97)
  * match color of arithmetic intensity points to corresponding bw lines
-  
+
 ## Omniperf 1.0.7 (21 Feb 2023)

  * update documentation (#52, #64)
@@ -126,7 +126,7 @@ Full documentation for ROCm Compute Profiler is available at [https://rocm.docs.
  * add MI100 configs to override rocprofiler's incomplete default (#75)
  * improve error message when no GPU(s) detected (#85)
  * separate CI tests by Linux distro and add status badges
-  
+
 ## Omniperf 1.0.6 (21 Dec 2022)

  * CI update: documentation now published via github action (#22)
@@ -148,8 +148,8 @@ Full documentation for ROCm Compute Profiler is available at [https://rocm.docs.
  * update python requirements.txt with minimum versions for numpy and pandas
  * addition of progress bar indicator in web-based GUI (#8)
  * reduced default content for web-based GUI to reduce load times (#9)
-  * minor packaging and CI updates 
-  * variety of documentation updates  
+  * minor packaging and CI updates
+  * variety of documentation updates
  * added an optional argument to vcopy.cpp workload example to specify device id

 ## Omniperf 1.0.3 (07 Nov 2022)
@@ -427,7 +427,6 @@ set(CPACK_PACKAGE_VERSION

 # RPM package specific variables
 set(CPACK_RPM_PACKAGE_LICENSE "MIT")
-set(CPACK_RPM_PACKAGE_PROVIDES "${CPACK_PACKAGE_NAME}")
 set(CPACK_RPM_COMPONENT_INSTALL ON)
 set(CPACK_RPM_PACKAGE_RELEASE_DIST ON)
 set(CPACK_RPM_FILE_NAME "RPM-DEFAULT")
@@ -449,6 +448,16 @@ set(PACKAGE_REQUIRES
 set(CPACK_RPM_PACKAGE_REQUIRES ${PACKAGE_REQUIRES})
 set(CPACK_DEBIAN_PACKAGE_DEPENDS ${PACKAGE_REQUIRES})

+# Handle the project rebranding from omniperf to rocprofiler-compute
+set(OMNIPERF_PACKAGE_NAME "omniperf")
+set(CPACK_RPM_PACKAGE_PROVIDES ${OMNIPERF_PACKAGE_NAME})
+set(CPACK_RPM_PACKAGE_OBSOLETES ${OMNIPERF_PACKAGE_NAME})
+set(CPACK_RPM_PACKAGE_CONFLICTS ${OMNIPERF_PACKAGE_NAME})
+
+set(CPACK_DEBIAN_PACKAGE_PROVIDES ${OMNIPERF_PACKAGE_NAME})
+set(CPACK_DEBIAN_PACKAGE_REPLACES ${OMNIPERF_PACKAGE_NAME})
+set(CPACK_DEBIAN_PACKAGE_BREAKS ${OMNIPERF_PACKAGE_NAME})
+
 # Disable automatic dependency generation
 set(CPACK_RPM_PACKAGE_AUTOREQPROV OFF)
 set(CPACK_RPM_PACKAGE_AUTOREQ OFF)
@@ -33,27 +33,27 @@ and apply your changes there.

 - Ensure the PR is based on the `amd-staging` branch of the ROCm Compute Profiler GitHub repository.

- ROCm Compute Profiler requires new commits to include a "Signed-off-by" token in the commit message (typically enabled via the `git commit -s` option), indicating your agreement to the projects's [Developer's Certificate of Origin](https://developercertificate.org/) and compatability with the project [LICENSE](LICENSE):
+> [!TIP]
+> To ensure you meet all formatting requirements before publishing, we recommend you utilize our included [*pre-commit hooks*](https://pre-commit.com/#introduction). For more information on how to use pre-commit hooks please see the [section below](#using-pre-commit-hooks).

+## Using pre-commit hooks

-> (a) The contribution was created in whole or in part by me and I
-> have the right to submit it under the open source license
-> indicated in the file; or
->
-> (b) The contribution is based upon previous work that, to the best
-> of my knowledge, is covered under an appropriate open source
-> license and I have the right under that license to submit that
-> work with modifications, whether created in whole or in part
-> by me, under the same open source license (unless I am
-> permitted to submit under a different license), as indicated
-> in the file; or
->
-> (c) The contribution was provided directly to me by some other
-> person who certified (a), (b) or (c) and I have not modified
-> it.
->
-> (d) I understand and agree that this project and the contribution
-> are public and that a record of the contribution (including all
-> personal information I submit with it, including my sign-off) is
-> maintained indefinitely and may be redistributed consistent with
-> this project or the open source license(s) involved.
+Our project supports optional [*pre-commit hooks*](https://pre-commit.com/#introduction) which developers can leverage to verify formatting before publishing their code. Once enabled, any commits you propose to the repository will be automatically checked for formatting. Initial setup is as follows:
+
+```console
+python3 -m pip install pre-commit
+cd rocprofiler-compute
+pre-commit install
+```
+
+Now, when you commit code to the repository you should see something like this:
+
+![A screen capture showing terminal output from a pre-commit hook](docs/data/contributing/pre-commit-hook.png)
+
+Please see the [pre-commit documentation](https://pre-commit.com/#quick-start) for additional information.
+
+## Coding guidelines
+
+Below are some repository specific guidelines which are followed througout the repository.
+Any future contributions should adhere to these guidelines:
+* Use pathlib library functions instead of os.path for manipulating file paths
@@ -8,7 +8,7 @@ Before publishing a new ROCm Compute Profiler release, please review this checkl
 2) **Sync `amd-mainline` with `amd-staging`**. A rebase may be required to pull all the desired patches from the development branch to our stable mainline. Click [here](https://github.com/ROCm/rocprofiler-compute/compare/amd-mainline...amd-staging) to begin that process.
 3) **Update [CHANGES](CHANGES)** to reflect all major modifications to the codebase since the last release. When modifying [CHANGES](CHANGES) please ensure formatting is consistent with the rest of the ROCm software stack. See [this template](https://github.com/ROCm/hipTensor/blob/develop/CHANGELOG.md) for reference.
 4) **Confirm all CI tests are passing**. You can easily confirm this by peeking the passing status of all GitHub continuous integration tests.
-5) **Create a tag from `amd-mainline`**. More information on tagging can be found at [Git Docs - Tagging](https://git-scm.com/book/en/v2/Git-Basics-Tagging). 
+5) **Create a tag from `amd-mainline`**. More information on tagging can be found at [Git Docs - Tagging](https://git-scm.com/book/en/v2/Git-Basics-Tagging).

 > [!NOTE]
 Note: A successful tag should trigger the [packaging action](.github/workflows/packaging.yml) which will produce a tarball artifact. **This artifact needs to be included as an asset in your release**. Please find that the [packaging action](.github/workflows/packaging.yml) will automatically create a draft release with your tarball attached.
@@ -29,4 +29,3 @@ prepend_path("PATH",binDir)
 if ( pythonDeps  ~= "" ) then
   prepend_path("PYTHONPATH",pythonDeps)
 end
-
@@ -51,4 +51,4 @@ RUN wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -
    conda init

 WORKDIR /home
-SHELL [ "/bin/bash", "--login", "-c" ]
+SHELL [ "/bin/bash", "--login", "-c" ]
@@ -49,4 +49,4 @@ WORKDIR /home
 ENV LC_ALL C.UTF-8
 SHELL [ "/bin/bash", "--login", "-c" ]
 COPY ./entrypoint-rhel.sh /docker-entrypoint.sh
-ENTRYPOINT [ "/docker-entrypoint.sh" ]
+ENTRYPOINT [ "/docker-entrypoint.sh" ]
@@ -54,4 +54,4 @@ RUN wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -

 ENV LC_ALL C.UTF-8
 WORKDIR /home
-SHELL [ "/bin/bash", "--login", "-c" ]
+SHELL [ "/bin/bash", "--login", "-c" ]
@@ -45,4 +45,4 @@ RUN apt-get update && \

 ENV LC_ALL C.UTF-8
 WORKDIR /home
-SHELL [ "/bin/bash", "--login", "-c" ]
+SHELL [ "/bin/bash", "--login", "-c" ]
@@ -151,4 +151,4 @@ if [ "${PUSH}" -gt 0 ]; then
    do
        verbose-run docker push ${USER}/rocprofiler-compute:ci-base-${DISTRO}-${VERSION}
    done
-fi
+fi
@@ -195,7 +195,7 @@ do
                *)
                    ;;
            esac
-            echo 
+            echo
            verbose-build docker build . ${PULL} --progress plain -f ${DOCKER_FILE} --tag ${CONTAINER} --build-arg DISTRO=${DISTRO} --build-arg VERSION=${VERSION} --build-arg ROCM_VERSION=${ROCM_VERSION} --build-arg ROCM_REPO_VERSION=${ROCM_REPO_VERSION} --build-arg ROCM_REPO_DIST=${ROCM_REPO_DIST} --build-arg PYTHON_VERSIONS=\"${PYTHON_VERSIONS}\"
        elif [ "${DISTRO}" = "rhel" ]; then
            if [ -z "${VERSION_MINOR}" ]; then
@@ -269,4 +269,4 @@ do
            docker push ${CONTAINER}
        fi
    done
-done
+done
@@ -2,4 +2,4 @@
 /_build
 /_doxygen
 /.gitinfo
-/omniperf.dox
+/omniperf.dox
@@ -17,4 +17,4 @@ help:
 # Catch-all target: route all unknown targets to Sphinx using the new
 # "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
 %: Makefile
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
@@ -276,7 +276,7 @@ Analyze
  ```

 - Customized profiling "System Speed-of-Light" and "CS_Busy" only
-  
+
  ```shell
  $ omniperf analyze -p workloads/vcopy/mi200/  -b 2  5.1.0
  ```
@@ -288,7 +288,7 @@ Analyze
  First, list the top kernels in your application using `--list-kernels`.
  ```shell-session
  $ omniperf analyze -p workloads/vcopy/mi200/ --list-kernels
-  
+
  --------
  Analyze
  --------
@@ -308,7 +308,7 @@ Analyze

  ```shell-session
  $ omniperf -p workloads/vcopy/mi200/ -k 0
-  
+
  --------
  Analyze
  --------
@@ -324,17 +324,17 @@ Analyze
  ╘════╧══════════════════════════════════════════╧═════════╧═══════════╧════════════╧══════════════╧════════╧═════╛
  ... ...
  ```
-  
+
  > Note: You'll see your filtered kernel(s) indicated by a asterisk in the Top Stats table


 - Baseline comparison
-  
+
  ```shell
  omniperf analyze -p workload1/path/  -p workload2/path/
  ```
  > Note: You can also apply diffrent filters to each workload.
-  
+
  OR
  ```shell
  omniperf analyze -p workload1/path/ -k 0  -p workload2/path/ -k 1
@@ -400,7 +400,7 @@ go to http://localhost:8050/ to see an analysis page.
 ![Standalone GUI Homepage](images/standalone_gui.png)

 ```{tip}
-To launch the web application on a port other than 8050, include an optional port argument:  
+To launch the web application on a port other than 8050, include an optional port argument:
 `--gui <desired port>`
 ```

@@ -429,7 +429,7 @@ The Omniperf Grafana GUI Analyzer supports the following features to facilitate

 - System and IP-Block Speed-of-Light (SOL)
 - Multiple normalization options, including per-cycle, per-wave, per-kernel and per-second.
- Baseline comparisons 
+- Baseline comparisons
 - Regex based Dispatch ID filtering
 - Roofline Analysis
 - Detailed per IP Block performance counters and metrics
@@ -456,25 +456,25 @@ Multiple performance number normalizations are provided to allow performance ins
 Omniperf enables baseline comparison to allow checking A/B effect. The current release limits the baseline comparison to the same SoC. Cross comparison between SoCs is in development.

 For both the Current Workload and the Baseline Workload, one can independently setup the following filters to allow fine grained comparions:
- Workload Name 
+- Workload Name
 - GPU ID filtering (multi selection)
 - Kernel Name filtering (multi selection)
 - Dispatch ID filtering (Regex filtering)
 - Omniperf Panels (multi selection)

 ##### Regex based Dispatch ID filtering
-This release enables regex based dispatch ID filtering to flexibly choose the kernel invocations. One may refer to [Regex Numeric Range Generator](https://3widgets.com/), to generate typical number ranges. 
+This release enables regex based dispatch ID filtering to flexibly choose the kernel invocations. One may refer to [Regex Numeric Range Generator](https://3widgets.com/), to generate typical number ranges.

 For example, if one wants to inspect Dispatch Range from 17 to 48, inclusive, the corresponding regex is : **(1[7-9]|[23]\d|4[0-8])**. The generated express can be copied over for filtering.

 ##### Incremental Profiling
 Omniperf supports incremental profiling to significantly speed up performance analysis.

-> Refer to [*IP Block profiling*](https://rocm.github.io/omniperf/profiling.html#ip-block-profiling) section for this command. 
+> Refer to [*IP Block profiling*](https://rocm.github.io/omniperf/profiling.html#ip-block-profiling) section for this command.

-By default, the entire application is profiled to collect perfmon counter for all IP blocks, giving a system level view of where the workload stands in terms of performance optimization opportunities and bottlenecks. 
+By default, the entire application is profiled to collect perfmon counter for all IP blocks, giving a system level view of where the workload stands in terms of performance optimization opportunities and bottlenecks.

-After that one may focus on only a few IP blocks, (e.g., L1 Cache or LDS) to closely check the effect of software optimizations, without performing application replay for all other IP Blocks. This saves lots of compute time. In addition, the prior profiling results for other IP blocks are not overwritten. Instead, they can be merged during the import to piece together the system view. 
+After that one may focus on only a few IP blocks, (e.g., L1 Cache or LDS) to closely check the effect of software optimizations, without performing application replay for all other IP Blocks. This saves lots of compute time. In addition, the prior profiling results for other IP blocks are not overwritten. Instead, they can be merged during the import to piece together the system view.

 ##### Color Coding
 The uniform color coding is applied to most visualizations (bars, table, diagrams etc). Typically, Yellow color means over 50%, while Red color mean over 90% percent, for easy inspection.
@@ -484,7 +484,7 @@ The uniform color coding is applied to most visualizations (bars, table, diagram
 ![Grafana GUI Global Variables](images/global_variables.png)

 #### Grafana GUI Import
-The omniperf database `--import` option imports the raw profiling data to Grafana's backend MongoDB database. This step is only required for Grafana GUI based performance analysis. 
+The omniperf database `--import` option imports the raw profiling data to Grafana's backend MongoDB database. This step is only required for Grafana GUI based performance analysis.

 Default username and password for MongoDB (to be used in database mode) are as follows:

@@ -503,23 +503,23 @@ When using database mode, be sure to tailor the connection options to the machin
 $ omniperf database --help
 ROC Profiler:  /usr/bin/rocprof

-usage: 
-                                        
+usage:
+
 omniperf database <interaction type> [connection options]

-                                        
+

 -------------------------------------------------------------------------------
-                                        
+
 Examples:
-                                        
+
        omniperf database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/
-                                        
+
        omniperf database --remove -H pavii1 -u temp -w omniperf_asw_sample_mi200
-                                        
+
 -------------------------------------------------------------------------------

-                                        
+

 Help:
  -h, --help             show this help message and exit
@@ -539,7 +539,7 @@ Connection Options:
  -p , --password                                       The user's password. (will be requested later if it's not set)
  -t , --team                                           Specify Team prefix.
  -w , --workload                                       Specify name of workload (to remove) or path to workload (to import)
-  -k , --kernelVerbose                                  Specify Kernel Name verbose level 1-5. 
+  -k , --kernelVerbose                                  Specify Kernel Name verbose level 1-5.
                                                        Lower the level, shorter the kernel name. (DEFAULT: 2) (DISABLE: 5)
 ```

@@ -547,11 +547,11 @@ Connection Options:
 ```shell-session
 $ omniperf database --import -H dummybox -u temp -t asw -w workloads/vcopy/mi200/
 ROC Profiler:  /usr/bin/rocprof
- 
+
 --------
 Import Profiling Results
 --------
- 
+
 Pulling data from  /home/amd/xlu/test/workloads/vcopy/mi200
 The directory exists
 Found sysinfo file
@@ -8,19 +8,20 @@

 # -- Path setup --------------------------------------------------------------

+import subprocess as sp
+import sys
+
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
-# documentation root, use os.path.abspath to make it absolute, like shown here.
+# documentation root, use str(Path(<rel_path>).absolute().resolve()) to make it absolute, like shown here.
 #
-import os
-import sys
-import subprocess as sp
+from pathlib import Path

-sys.path.insert(0, os.path.abspath(".."))
+sys.path.insert(0, str(Path("..").absolute().resolve()))

 repo_version = "unknown"
 # Determine short version by file in repo
-if os.path.isfile("./VERSION"):
+if Path("./VERSION").is_file():
    with open("./VERSION") as f:
        repo_version = f.readline().strip()

@@ -12,7 +12,7 @@ In order to interact with the Grafana GUI you must sync data with the MongoDB ba

 Simply pass the directory of your desired workload like so,
 ```shell
-$ omniperf database --import -w <path-to-results> -H <hostname> -u <username> -t <team-name> 
+$ omniperf database --import -w <path-to-results> -H <hostname> -u <username> -t <team-name>
 ```
 **2. python ast error: 'Constant' object has no attribute 'kind'**

@@ -44,12 +44,12 @@ This pop up will appear

   Local clients
   - Forwarded Port: [PORT]
-   
+
   Remote Server
   - Remote Server: localhost
   - Remote Port: [PORT]
-   
+
   SSH Server
   - SSH server: Name of the server one is connecting to
   - SSH login: Username to login to the server
-   - SSH port: 22
+   - SSH port: 22
@@ -9,7 +9,7 @@
 ## Quickstart

 1. **Launch & Profile the target application with the command line profiler**
-   
+
    The command line profiler launches the target application, calls the rocProfiler API, and collects profile results for the specified kernels, dispatches, and/or IP blocks.  If not specified, Omniperf will default to collecting all available counters for all kernels/dispatches launched by the user's executable.

    To collect the default set of data for all kernels in the target application, launch, e.g.:
@@ -19,7 +19,7 @@
    The app runs, each kernel is launched, and profiling results are generated. By default, results are written to (e.g.,) ./workloads/vcopy_data (configurable via the `-n` argument). To collect all requested profile information, it may be required to replay kernels multiple times.

 2. **Customize data collection**
-    
+
    Options are available to specify for which kernels/metrics data should be collected.
    Note that filtering can be applied either in the profiling or analysis stage, however filtering at during profiling collection will often speed up your overall profiling run time.

@@ -34,7 +34,7 @@
    ```

 3. **Analyze at the command line**
-   
+
   After generating a local output folder (./workloads/\<name>), the command line tool can also be used to quickly interface with profiling results. View different metrics derived from your profiled results and get immediate access all metrics organized by IP block.

   If no kernel, dispatch, or ipblock filters are applied at this stage, analysis will be reflective of the entirety of the profiling data.
@@ -42,7 +42,7 @@
   To interact with profiling results from a different session, users just provide the workload path.  `-p`/`--path` enables users to analyze existing profiling data in the Omniperf CLI.

 4. **Analyze in the Grafana GUI**
-   
+
   To conduct a more in-depth analysis of profiling results we recommend users utilize the Omniperf Grafana GUI. To interact with profiling results, users must import their data to the MongoDB instance included in the Omniperf dockerfile.

    To interact with Grafana GUI data, stored in the Omniperf DB, users can enter ***database*** mode. For example:
@@ -90,4 +90,4 @@ Standalone roofline analysis | profile | `--name`, `--roof-only`, `-- <profile_c
 Import a workload to database | database | `--import`, `--host`, `--username`, `--workload`, `--team`
 Remove a workload from database | database | `--remove`, `--host`, `--username`, `--workload`, `--team`
 Launch standalone GUI from CLI | analyze | `--path`, `--gui`
-Interact with profiling results from CLI | analyze | `--path`
+Interact with profiling results from CLI | analyze | `--path`
@@ -10,7 +10,7 @@ The [Omniperf](https://github.com/ROCm/omniperf) Tool is architecturally compose

 - **Omniperf Profiling**: Acquire raw performance counters via application replay based on the [rocProfiler](https://rocm.docs.amd.com/projects/rocprofiler/en/latest/rocprof.html).  The counters are stored in a comma-seperated value, for further analyis. A set of MI200 specific micro benchmarks are also run to acquire the hierarchical roofline data. The roofline model is not available on earlier accelerators.

- **Omniperf Grafana Analyzer**: 
+- **Omniperf Grafana Analyzer**:
  - *Grafana database import*: All raw performance counters are imported into the backend MongoDB database for Grafana GUI analysis and visualization. Compatibility of previously generated data between Omniperf versions is not necessarily guarenteed.
  - *Grafana GUI Analyzer*: A Grafana dashboard is designed to retrieve the raw counters info from the backend database. It also creates the relevant performance metrics and visualization.
 - **Omniperf Standalone GUI Analyzer**: A standalone GUI is provided to enable performance analysis without importing data into the backend database.
@@ -18,4 +18,3 @@ The [Omniperf](https://github.com/ROCm/omniperf) Tool is architecturally compose
 ![Omniperf Architectual Diagram](images/omniperf_server_vs_client_install.png)

 > Note: To learn more about the client vs. server model of Omniperf and our install process please see the [Deployment section](./installation.md) of the docs.
-
@@ -33,7 +33,7 @@ Omniperf client-side requires the following basic software dependencies prior to

 In addition, Omniperf leverages a number of Python packages that are
 documented in the top-level `requirements.txt` file.  These must be
-installed prior to Omniperf configuration.  
+installed prior to Omniperf configuration.

 The recommended procedure for Omniperf usage is to install into a shared file system so that multiple users can access the final installation.  The following steps illustrate how to install the necessary python dependencies using [pip](https://packaging.python.org/en/latest/) and Omniperf into a shared location controlled by the `INSTALL_DIR` environment variable.

@@ -167,7 +167,7 @@ Once you've decided which machine you'd like to use to host the Grafana and Mong
 ### 1) Install MongoDB Utils
 Omniperf uses [mongoimport](https://www.mongodb.com/docs/database-tools/mongoimport/) to upload data to Grafana's backend database. Install for Ubuntu 20.04 is as follows:

-```bash 
+```bash
 $ wget https://fastdl.mongodb.org/tools/db/mongodb-database-tools-ubuntu2004-x86_64-100.6.1.deb
 $ sudo apt install ./mongodb-database-tools-ubuntu2004-x86_64-100.6.1.deb
 ```
@@ -240,4 +240,3 @@ After a workload has been successfully uploaded, you should be able to select it
 ![Selecting Grafana workload](images/grafana_workload_selection.png)

 For more information on how to use the Grafana interface for anlysis please see the [Grafana section](./analysis.md#grafana-based-gui) in the Analyze Mode tab.
-
@@ -15,8 +15,8 @@ MI Performance Profiler ([Omniperf](https://github.com/ROCm/omniperf)) is a syst
 ## Features

 The Omniperf tool performs system profiling based on all available hardware counters for the target accelerator. It provides high level performance analysis features including System Speed-of-Light, IP block Speed-of-Light, Memory Chart Analysis, Roofline Analysis, Baseline Comparisons, and more...
-  
-Both command line analysis and GUI analysis are supported. 
+
+Both command line analysis and GUI analysis are supported.

 Detailed Feature List:
 - MI100 support
@@ -54,4 +54,3 @@ Detailed Feature List:
 | MI100    | Supported      |
 | MI200    | Supported      |
 | MI300    | In development |
-
@@ -138,21 +138,21 @@ RPL: output dir '/tmp/rpl_data_230411_165021_26406'
 RPL: result dir '/tmp/rpl_data_230411_165021_26406/input0_results_230411_165021'
 Finished allocating vectors on the CPU
 ROCProfiler: input from "/tmp/rpl_data_230411_165021_26406/input0.xml"
-  gpu_index = 
-  kernel = 
-  range = 
+  gpu_index =
+  kernel =
+  range =
  3 metrics
    SQ_INSTS_SMEM, SQ_INST_LEVEL_SMEM, SQ_ACCUM_PREV_HIRES
 Finished allocating vectors on the GPU
 Finished copying vectors to the GPU
-sw thinks it moved 1.000000 KB per wave 
+sw thinks it moved 1.000000 KB per wave
 Total threads: 1048576, Grid Size: 4096 block Size:256, Wavefronts:16384:
 Launching the  kernel on the GPU
 Finished executing kernel
 Finished copying the output vector from the GPU to the CPU
 Releasing GPU memory
 Releasing CPU memory
- 
+
 ... ...
 ROCPRofiler: 1 contexts collected, output directory /tmp/rpl_data_220527_130317_1787038/input_results_220527_130317
 File 'workloads/vcopy/mi200/timestamps.csv' is generating
@@ -321,14 +321,14 @@ RPL: output dir '/tmp/rpl_data_230411_170300_29696'
 RPL: result dir '/tmp/rpl_data_230411_170300_29696/input0_results_230411_170300'
 Finished allocating vectors on the CPU
 ROCProfiler: input from "/tmp/rpl_data_230411_170300_29696/input0.xml"
-  gpu_index = 
+  gpu_index =
  kernel = vecCopy
- 
+
 ... ...
 ```

 #### Dispatch Filtering
-Dispatch filtering is based on the *global* dispatch index of kernels in a run. 
+Dispatch filtering is based on the *global* dispatch index of kernels in a run.

 The following example profiles only the 0th dispatched kernel in execution of the application:
 ```shell-session
@@ -358,8 +358,8 @@ RPL: output dir '/tmp/rpl_data_230411_170356_30314'
 RPL: result dir '/tmp/rpl_data_230411_170356_30314/input0_results_230411_170356'
 Finished allocating vectors on the CPU
 ROCProfiler: input from "/tmp/rpl_data_230411_170356_30314/input0.xml"
-  gpu_index = 
-  kernel = 
+  gpu_index =
+  kernel =
  range = 0
 ...
 ```
@@ -367,7 +367,7 @@ ROCProfiler: input from "/tmp/rpl_data_230411_170356_30314/input0.xml"


 ### Standalone Roofline
-If you're only interested in generating roofline analysis data try using `--roof-only`. This will only collect counters relevent to roofline, as well as generate a standalone .pdf output of your roofline plot. 
+If you're only interested in generating roofline analysis data try using `--roof-only`. This will only collect counters relevent to roofline, as well as generate a standalone .pdf output of your roofline plot.

 Standalone Roofline Options:

@@ -422,4 +422,4 @@ drwxrwxr-x 2 colramos colramos  4096 Apr 11 17:16 perfmon
 ```
 A sample *empirRoof_gpu-ALL_fp32.pdf* looks something like this:

-![Sample Standalone Roof Plot](images/sample-roof-plot.png)
+![Sample Standalone Roof Plot](images/sample-roof-plot.png)
@@ -2,4 +2,4 @@
 /_build
 /_doxygen
 /.gitinfo
-/omniperf.dox
+/omniperf.dox
@@ -28,17 +28,17 @@ Run `omniperf analyze -h` for more details.

 ### Demo

-1) To begin, generate a high-level analysis report utilizing Omniperf's `-b` (a.k.a. `--block`) flag. 
+1) To begin, generate a high-level analysis report utilizing Omniperf's `-b` (a.k.a. `--block`) flag.
 ```shell-session
 $ omniperf analyze -p workloads/vcopy/MI200/ -b 2


-  ___                  _                  __ 
+  ___                  _                  __
 / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
+| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
 | |_| | | | | | | | | | | |_) |  __/ |  |  _|
- \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                        |_|                  
+ \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
+                        |_|

 Analysis mode = cli
 [analysis] deriving Omniperf metrics...
@@ -135,12 +135,12 @@ Analysis mode = cli
 ```shell-session
 $ omniperf analyze -p workloads/vcopy/MI200/ --list-metrics gfx90a

-  ___                  _                  __ 
+  ___                  _                  __
 / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
+| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
 | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-\___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                        |_|                  
+\___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
+                        |_|

 Analysis mode = cli
 [analysis] deriving Omniperf metrics...
@@ -289,7 +289,7 @@ Some cells may be blank indicating a missing/unavailable hardware counter or NUL
  ```

 - __Show "System Speed-of-Light" and "CS_Busy" blocks only__
-  
+
  ```shell
  $ omniperf analyze -p workloads/vcopy/MI200/  -b 2  5.1.0
  ```
@@ -303,7 +303,7 @@ Some cells may be blank indicating a missing/unavailable hardware counter or NUL
  First, list the top kernels in your application using `--list-stats`.
  ```shell-session
  $ omniperf analyze -p workloads/vcopy/MI200/ --list-stats
-  
+
  Analysis mode = cli
  [analysis] deriving Omniperf metrics...

@@ -329,7 +329,7 @@ Some cells may be blank indicating a missing/unavailable hardware counter or NUL

  ```shell-session
  $ omniperf analyze -p workloads/vcopy/MI200/ -k 0
-  
+
  Analysis mode = cli
  [analysis] deriving Omniperf metrics...

@@ -344,14 +344,14 @@ Some cells may be blank indicating a missing/unavailable hardware counter or NUL
  ╘════╧══════════════════════════════════════════╧═════════╧═══════════╧════════════╧══════════════╧════════╧═════╛
  ... ...
  ```
-  
+
  ```{note}
  You will see your filtered kernel(s) indicated by an asterisk in the Top Stats table
  ```


 - __Baseline comparison__
-  
+
  ```shell
  omniperf analyze -p workload1/path/  -p workload2/path/
  ```
@@ -396,12 +396,12 @@ To launch the standalone GUI, include the `--gui` flag with your desired analysi
 ```shell-session
 $ omniperf analyze -p workloads/vcopy/MI200/ --gui

-  ___                  _                  __ 
+  ___                  _                  __
 / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
+| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
 | |_| | | | | | | | | | | |_) |  __/ |  |  _|
- \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                        |_|                  
+ \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
+                        |_|

 Analysis mode = web_ui
 [analysis] deriving Omniperf metrics...
@@ -426,7 +426,7 @@ go to http://localhost:8050/ to see an analysis page.
 ![Standalone GUI Homepage](images/standalone_gui.png)

 ```{tip}
-To launch the web application on a port other than 8050, include an optional port argument:  
+To launch the web application on a port other than 8050, include an optional port argument:
 `--gui <desired port>`
 ```

@@ -455,7 +455,7 @@ The Omniperf Grafana GUI Analyzer supports the following features to facilitate

 - System and Hardware Component (Hardware Block) Speed-of-Light (SOL)
 - Multiple normalization options, including per-cycle, per-wave, per-kernel and per-second.
- Baseline comparisons 
+- Baseline comparisons
 - Regex based Dispatch ID filtering
 - Roofline Analysis
 - Detailed performance counters and metrics per hardware component, e.g.,
@@ -482,7 +482,7 @@ Multiple performance number normalizations are provided to allow performance ins
 Omniperf enables baseline comparison to allow checking A/B effect. Currently baseline comparison is limited to the same SoC. Cross comparison between SoCs is in development.

 For both the Current Workload and the Baseline Workload, one can independently setup the following filters to allow fine grained comparisons:
- Workload Name 
+- Workload Name
 - GPU ID filtering (multi-selection)
 - Kernel Name filtering (multi-selection)
 - Dispatch ID filtering (Regex filtering)
@@ -498,7 +498,7 @@ Omniperf supports incremental profiling to significantly speed up performance an

 > Refer to [*Hardware Component Filtering*](profiling.md#hardware-component-filtering) section for this command.

-By default, the entire application is profiled to collect performance counters for all hardware blocks, giving a complete view of where the workload stands in terms of performance optimization opportunities and bottlenecks. 
+By default, the entire application is profiled to collect performance counters for all hardware blocks, giving a complete view of where the workload stands in terms of performance optimization opportunities and bottlenecks.

 After that one may focus on only a few hardware components, (e.g., L1 Cache or LDS) to closely check the effect of software optimizations, without performing application replay for all other hardware components. This saves lots of compute time. In addition, the prior profiling results for other hardware components are not overwritten. Instead, they can be merged during the import to piece together the system view.

@@ -510,7 +510,7 @@ The uniform color coding is applied to most visualizations (bars, table, diagram
 ![Grafana GUI Global Variables](images/global_variables.png)

 #### Grafana GUI Import
-The omniperf database `--import` option imports the raw profiling data to Grafana's backend MongoDB database. This step is only required for Grafana GUI based performance analysis. 
+The omniperf database `--import` option imports the raw profiling data to Grafana's backend MongoDB database. This step is only required for Grafana GUI based performance analysis.

 Default username and password for MongoDB (to be used in database mode) are as follows:

@@ -527,23 +527,23 @@ When using database mode, be sure to tailor the connection options to the machin

 ```shell-session
 $ omniperf database --help
-usage: 
-            
+usage:
+
 omniperf database <interaction type> [connection options]

-            
+

 -------------------------------------------------------------------------------
-            
+
 Examples:
-            
+
        omniperf database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/
-            
+
        omniperf database --remove -H pavii1 -u temp -w omniperf_asw_sample_mi200
-            
+
 -------------------------------------------------------------------------------

-        
+

 Help:
  -h, --help         show this help message and exit
@@ -571,14 +571,14 @@ Connection Options:
 ```shell-session
 $ omniperf database --import -H dummybox -u temp -t asw -w workloads/vcopy/mi200/

-  ___                  _                  __ 
+  ___                  _                  __
 / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
+| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
 | |_| | | | | | | | | | | |_) |  __/ |  |  _|
- \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                        |_|                  
+ \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
+                        |_|
+

- 
 Pulling data from  /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
 The directory exists
 Found sysinfo file
@@ -8,19 +8,20 @@

 # -- Path setup --------------------------------------------------------------

+import subprocess as sp
+import sys
+
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
-# documentation root, use os.path.abspath to make it absolute, like shown here.
+# documentation root, use str(Path(<rel_path>).absolute().resolve()) to make it absolute, like shown here.
 #
-import os
-import sys
-import subprocess as sp
+from pathlib import Path

-sys.path.insert(0, os.path.abspath(".."))
+sys.path.insert(0, str(Path("..").absolute().resolve()))

 repo_version = "unknown"
 # Determine short version by file in repo
-if os.path.isfile("./VERSION"):
+if Path("./VERSION").is_file():
    with open("./VERSION") as f:
        repo_version = f.readline().strip()

@@ -12,7 +12,7 @@ In order to interact with the Grafana GUI you must sync data with the MongoDB ba

 Simply pass the directory of your desired workload like so,
 ```shell
-$ omniperf database --import -w <path-to-results> -H <hostname> -u <username> -t <team-name> 
+$ omniperf database --import -w <path-to-results> -H <hostname> -u <username> -t <team-name>
 ```
 **2. python ast error: 'Constant' object has no attribute 'kind'**

@@ -56,11 +56,11 @@ This pop up will appear

   Local clients
   - Forwarded Port: [PORT]
-   
+
   Remote Server
   - Remote Server: localhost
   - Remote Port: [PORT]
-   
+
   SSH Server
   - SSH server: Name of the server one is connecting to
   - SSH login: Username to login to the server
@@ -17,7 +17,7 @@
    $ omniperf profile -n vcopy_data -- ./vcopy -n 1048576 -b 256
    ```
    The app runs, each kernel is launched, and profiling results are generated. By default, results are written to a subdirectory with your accelerator's name e.g., ./workloads/vcopy_data/MI200/ (where name is configurable via the `-n` argument).
-    
+
    ```{note}
    To collect all requested profile information, it may be required to replay kernels multiple times.
    ```
@@ -86,7 +86,7 @@ Modes change the fundamental behavior of the Omniperf command line tool. Dependi
    $ omniperf database --help
    ```
 ### Global Options
-The Omniperf command line tool has a set of 'global' options that are available across all modes. 
+The Omniperf command line tool has a set of 'global' options that are available across all modes.

 | Argument           | Description                                                       |
 | :----------------- | :---------------------------------------------------------------- |
@@ -10,7 +10,7 @@ The [Omniperf](https://github.com/ROCm/omniperf) Tool is architecturally compose

 - **Omniperf Profiling**: Acquire raw performance counters via application replay based on [rocProf](https://rocm.docs.amd.com/projects/rocprofiler/en/latest/rocprof.html). The counters are stored in a comma-separated format, for further analysis. A set of MI200 specific micro benchmarks are also run to acquire the hierarchical roofline data. The roofline model is not available on earlier accelerators.

- **Omniperf Grafana Analyzer**: 
+- **Omniperf Grafana Analyzer**:
  - *Grafana database import*: All raw performance counters are imported into the backend MongoDB database for Grafana GUI analysis and visualization. Compatibility of previously generated data between Omniperf versions is not necessarily guaranteed.
  - *Grafana GUI Analyzer*: A Grafana dashboard is designed to retrieve the raw counters info from the backend database. It also creates the relevant performance metrics and visualization.
 - **Omniperf Standalone GUI Analyzer**: A standalone GUI is provided to enable performance analysis without importing data into the backend database.
@@ -1 +1 @@
-<svg id="Layer_1" data-name="Layer 1" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 139.72 33.32"><defs><style>.cls-1{fill:#fff;}</style></defs><title>AMD-logo-white-v2</title><path class="cls-1" d="M33,31.14H25.21l-2.37-5.72H9.92L7.76,31.14H.14L11.78,2.26h8.34Zm-16.89-22L11.83,20.39h8.89Z" transform="translate(-0.14 -0.03)"/><path class="cls-1" d="M61.1,2.26h6.27V31.14h-7.2v-18l-7.79,9.06h-1.1L43.49,13.1v18h-7.2V2.26h6.27L51.83,13Z" transform="translate(-0.14 -0.03)"/><path class="cls-1" d="M85.61,2.26c10.54,0,16,6.56,16,14.48,0,8.3-5.25,14.4-16.77,14.4H72.86V2.26ZM80.06,25.85h4.7c7.24,0,9.4-4.91,9.4-9.15,0-5-2.67-9.15-9.48-9.15H80.06Z" transform="translate(-0.14 -0.03)"/><polygon class="cls-1" points="130.64 9.08 115.75 9.08 106.68 0 139.72 0 139.72 33.05 130.64 23.97 130.64 9.08"/><polygon class="cls-1" points="115.74 23.98 115.74 10.9 106.4 20.24 106.4 33.33 119.48 33.33 128.82 23.98 115.74 23.98"/></svg>
+<svg id="Layer_1" data-name="Layer 1" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 139.72 33.32"><defs><style>.cls-1{fill:#fff;}</style></defs><title>AMD-logo-white-v2</title><path class="cls-1" d="M33,31.14H25.21l-2.37-5.72H9.92L7.76,31.14H.14L11.78,2.26h8.34Zm-16.89-22L11.83,20.39h8.89Z" transform="translate(-0.14 -0.03)"/><path class="cls-1" d="M61.1,2.26h6.27V31.14h-7.2v-18l-7.79,9.06h-1.1L43.49,13.1v18h-7.2V2.26h6.27L51.83,13Z" transform="translate(-0.14 -0.03)"/><path class="cls-1" d="M85.61,2.26c10.54,0,16,6.56,16,14.48,0,8.3-5.25,14.4-16.77,14.4H72.86V2.26ZM80.06,25.85h4.7c7.24,0,9.4-4.91,9.4-9.15,0-5-2.67-9.15-9.48-9.15H80.06Z" transform="translate(-0.14 -0.03)"/><polygon class="cls-1" points="130.64 9.08 115.75 9.08 106.68 0 139.72 0 139.72 33.05 130.64 23.97 130.64 9.08"/><polygon class="cls-1" points="115.74 23.98 115.74 10.9 106.4 20.24 106.4 33.33 119.48 33.33 128.82 23.98 115.74 23.98"/></svg>
@@ -684,7 +684,7 @@
           y="240.85156"
           id="tspan43344"><tspan
             style="text-align:center;text-anchor:middle"
-             id="tspan43342">Atomic 
+             id="tspan43342">Atomic
 </tspan></tspan><tspan
           x="134.80859"
           y="260.85156"
@@ -181,7 +181,7 @@ Once you have decided which machine you would like to use to host the Grafana an
 #### Install MongoDB Utils
 Omniperf uses [mongoimport](https://www.mongodb.com/docs/database-tools/mongoimport/) to upload data to Grafana's backend database. Install for Ubuntu 20.04 is as follows:

-```bash 
+```bash
 $ wget https://fastdl.mongodb.org/tools/db/mongodb-database-tools-ubuntu2004-x86_64-100.6.1.deb
 $ sudo apt install ./mongodb-database-tools-ubuntu2004-x86_64-100.6.1.deb
 ```
@@ -265,4 +265,3 @@ After a workload has been successfully uploaded, you should be able to select it
 ![Selecting Grafana workload](images/grafana_workload_selection.png)

 For more information on how to use the Grafana interface for analysis please see the [Grafana section](./analysis.md#grafana-based-gui) in the Analyze Mode tab.
-
@@ -96,7 +96,7 @@ The SIMDs in the [VALU](valu) are connected to the LDS in pairs (see above).
 Only one SIMD per pair may issue an LDS instruction at a time, but both pairs may issue concurrently.

 On CDNA accelerators, the LDS contains 32 banks and each bank is 4B wide.
-The LDS is designed such that each bank can be read from/written to/atomically updated every cycle, for a total throughput of 128B/clock ([GCN Crash Course](https://www.slideshare.net/DevCentralAMD/gs4106-the-amd-gcn-architecture-a-crash-course-by-layla-mah), slide 40). 
+The LDS is designed such that each bank can be read from/written to/atomically updated every cycle, for a total throughput of 128B/clock ([GCN Crash Course](https://www.slideshare.net/DevCentralAMD/gs4106-the-amd-gcn-architecture-a-crash-course-by-layla-mah), slide 40).

 On each of the two ports to the SIMDs, 64B can be sent in each direction per cycle. So, a single wavefront, coming from one of the 2 SIMDs in a pair, can only get back 64B/cycle (16 lanes per cycle). The input port is shared between data and address and this can affect achieved bandwidth for different data sizes. For example, a 64-wide store where each lane is sending a 4B value takes 8 cycles (50% peak bandwidth) while a 64-wide store where each lane is sending a 16B value takes 20 cycles (80% peak bandwidth).

@@ -270,7 +270,7 @@ The wavefront runtime statistics gives a high-level overview of the execution of

 ```{list-table}
 :header-rows: 1
-:widths: 18 65 17 
+:widths: 18 65 17
 :class: noscroll-table
 * - Metric
  - Description
@@ -1481,7 +1481,7 @@ The Scalar L1D speed-of-light chart shows some key metrics of the sL1D cache as
  - Description
  - Unit
 * - Bandwidth
-  - The number of bytes looked up in the sL1D cache, as a percent of the peak theoretical bandwidth. Calculated as the ratio of sL1D requests over the [total sL1D cycles](TotalSL1DCycles). 
+  - The number of bytes looked up in the sL1D cache, as a percent of the peak theoretical bandwidth. Calculated as the ratio of sL1D requests over the [total sL1D cycles](TotalSL1DCycles).
  - Percent
 * - Cache Hit Rate
  - The percent of sL1D requests that hit{sup}`1` on a previously loaded line in the cache. Calculated as the ratio of the number of sL1D requests that hit over the number of all sL1D requests.
@@ -1601,7 +1601,7 @@ The L1 Instruction Cache speed-of-light chart shows some key metrics of the L1I
  - Description
  - Unit
 * - Bandwidth
-  - The number of bytes looked up in the L1I cache, as a percent of the peak theoretical bandwidth. Calculated as the ratio of L1I requests over the [total L1I cycles](TotalL1ICycles). 
+  - The number of bytes looked up in the L1I cache, as a percent of the peak theoretical bandwidth. Calculated as the ratio of L1I requests over the [total L1I cycles](TotalL1ICycles).
  - Percent
 * - Cache Hit Rate
  - The percent of L1I requests that hit on a previously loaded line the cache. Calculated as the ratio of the number of L1I requests that hit{sup}`1` over the number of all L1I requests.
@@ -1822,10 +1822,10 @@ The command processor's metrics therefore are focused on reporting, e.g.:
  - Percent of total cycles counted by the CPF-[L2](L2) interface where the CPF-L2 interface was active doing any work.  The ratio of CPF-L2 busy cycles over total cycles counted by the CPF-L2.
  - Percent
 * - CPF-L2 Stall
-  - Percent of CPF-L2 busy cycles where the CPF-[L2](L2) interface was stalled for any reason. 
+  - Percent of CPF-L2 busy cycles where the CPF-[L2](L2) interface was stalled for any reason.
  - Percent
 * - CPF-UTCL1 Stall
-  - Percent of CPF busy cycles where the CPF was stalled by address translation. 
+  - Percent of CPF busy cycles where the CPF was stalled by address translation.
  - Percent
 ```

@@ -1958,10 +1958,10 @@ Finally, the system speed-of-light summarizes some of the key metrics from vario
  - The percent of sL1D requests that hit on a previously loaded line the cache. Calculated as the ratio of the number of sL1D requests that hit over the number of all sL1D requests.
  - Percent
 * - [sL1D](sL1D) Bandwidth
-  - The number of bytes looked up in the sL1D cache per unit time. This is also presented as a percent of the peak theoretical bandwidth achievable on the specific accelerator. 
+  - The number of bytes looked up in the sL1D cache per unit time. This is also presented as a percent of the peak theoretical bandwidth achievable on the specific accelerator.
  - GB/s
 * - [L1I](L1I) Bandwidth
-  - The number of bytes looked up in the L1I cache per unit time. This is also presented as a percent of the peak theoretical bandwidth achievable on the specific accelerator. 
+  - The number of bytes looked up in the L1I cache per unit time. This is also presented as a percent of the peak theoretical bandwidth achievable on the specific accelerator.
  - GB/s
 * - [L1I](L1I) Cache Hit Rate
  - The percent of L1I requests that hit on a previously loaded line the cache. Calculated as the ratio of the number of L1I requests that hit over the number of all L1I requests.
@@ -2170,7 +2170,7 @@ These memory types include:
    - Memory that will be cached by the accelerator, but may be invalidated by writes from remote devices at kernel boundaries / after software-driven synchronization events. On [MI2XX](2xxnote) accelerators, this corresponds to "coarse-grained" memory allocated locally to the accelerator, using e.g., the default `hipMalloc` allocator.
 ```

-A good discussion of coarse and fine grained memory allocations and what type of memory is returned by various combinations of memory allocators, flags and arguments can be found in the [Crusher Quick-Start Guide](https://docs.olcf.ornl.gov/systems/crusher_quick_start_guide.html#floating-point-fp-atomic-operations-and-coarse-fine-grained-memory-allocations). 
+A good discussion of coarse and fine grained memory allocations and what type of memory is returned by various combinations of memory allocators, flags and arguments can be found in the [Crusher Quick-Start Guide](https://docs.olcf.ornl.gov/systems/crusher_quick_start_guide.html#floating-point-fp-atomic-operations-and-coarse-fine-grained-memory-allocations).

 (profiling-with-omniperf)=
 # Profiling with Omniperf by Example
@@ -2719,7 +2719,7 @@ $ omniperf analyze -p workloads/fine_grained_host_writes/mi200 -b 17.2.4 17.2.5
 ```

 Here we notice a few changes in our request pattern:
-  - As expected, the requests have changed from 64B Reads to 64B Write requests (17.5.7), 
+  - As expected, the requests have changed from 64B Reads to 64B Write requests (17.5.7),
  - these requests are homed in on a "remote" destination (17.2.6, 17.5.9), as expected, and,
  - these are also counted as a single Uncached Write request (17.5.6).

@@ -2978,7 +2978,7 @@ As discussed [previously](Flat_design), our `generic_write` kernel uses an addre

 We also note that the `filter` parameter passed in as a kernel argument (see [example](https://github.com/ROCm/omniperf/blob/amd-mainline/sample/vmem.hip), or [design note](Flat_design)) is set to zero on the host, such that we always write to the 'local' (LDS) memory allocation `lds`.

-Examining this kernel in the VMEM Instruction Mix table yields: 
+Examining this kernel in the VMEM Instruction Mix table yields:

 ```shell-session
 $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 2 -b 10.3 -n per_kernel
@@ -3749,7 +3749,7 @@ $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 10 -b 11.2
 ```

 Here we see that:
-  - both our IPC (11.2.0) and Issued IPC (11.2.1) are $\sim1.0$ as expected, and, 
+  - both our IPC (11.2.0) and Issued IPC (11.2.1) are $\sim1.0$ as expected, and,
  - the SALU Utilization (11.2.2) was nearly 100% as it was active for almost the entire kernel.

 (VALU_Active_Threads)=
@@ -4034,7 +4034,7 @@ The bank conflict rate linearly increases with the number of work-items within a


 (Occupancy_example)=
-## Occupancy Limiters Example 
+## Occupancy Limiters Example


 In this [example](https://github.com/ROCm/omniperf/blob/amd-mainline/sample/occupancy.hip), we will investigate the use of the resource allocation panel in the [Workgroup Manager](SPI)'s metrics section to determine occupancy limiters.
@@ -4180,7 +4180,7 @@ denotes the divide between `VGPRs` and `AGPRs`.
 Next, we examine our wavefront occupancy (2.1.15), and see that we are reaching only $\sim50\%$ of peak occupancy.
 As a result, we see that:
  - We are not scheduling workgroups $\sim25\%$ of [total scheduler-pipe cycles](TotalPipeCycles) (6.2.1); recall from the discussion of the [Workgroup manager](SPI), 25\% is the maximum.
-  - The scheduler-pipe is stalled (6.2.2) from scheduling workgroups due to resource constraints for the same $\sim25\%$ of the time. 
+  - The scheduler-pipe is stalled (6.2.2) from scheduling workgroups due to resource constraints for the same $\sim25\%$ of the time.
  - And finally, $\sim91\%$ of those stalls are due to a lack of SIMDs with the appropriate number of VGPRs available (6.2.5).

 That is, the reason we can't reach full occupancy is due to our VGPR usage, as expected!
@@ -4407,4 +4407,3 @@ Finally, we inspect the occupancy limiter metrics and see a roughly even split b

 This is yet another reminder to view occupancy holistically.
 While these metrics tell you why a workgroup cannot be scheduled, they do _not_ tell you what your occupancy was (consult wavefront occupancy) _nor_ whether increasing occupancy will be beneficial to performance.
-
@@ -28,7 +28,7 @@ vcopy testing on GCD 0
 Finished allocating vectors on the CPU
 Finished allocating vectors on the GPU
 Finished copying vectors to the GPU
-sw thinks it moved 1.000000 KB per wave 
+sw thinks it moved 1.000000 KB per wave
 Total threads: 1048576, Grid Size: 4096 block Size:256, Wavefronts:16384:
 Launching the  kernel on the GPU
 Finished executing kernel
@@ -56,12 +56,12 @@ The following sample command profiles the *vcopy* workload.
 ```shell-session
 $ omniperf profile --name vcopy -- ./vcopy -n 1048576 -b 256

-  ___                  _                  __ 
+  ___                  _                  __
 / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
+| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
 | |_| | | | | | | | | | | |_) |  __/ |  |  _|
- \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                        |_|                  
+ \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
+                        |_|

 Omniperf version: 2.0.0
 Profiler choice: rocprofv1
@@ -99,13 +99,13 @@ Collecting Performance Counters
   |-> [rocprof] Finished copying the output vector from the GPU to the CPU
   |-> [rocprof] Releasing GPU memory
   |-> [rocprof] Releasing CPU memory
-   |-> [rocprof] 
+   |-> [rocprof]
   |-> [rocprof] ROCPRofiler: 1 contexts collected, output directory /tmp/rpl_data_240312_174329_692890/input0_results_240312_174329
   |-> [rocprof] File '/home/auser/repos/omniperf/sample/workloads/vcopy/MI200/SQ_IFETCH_LEVEL.csv' is generating
-   |-> [rocprof] 
+   |-> [rocprof]
 [profiling] Current input file: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200/perfmon/SQ_INST_LEVEL_LDS.txt

-... 
+...

 [roofline] Checking for roofline.csv in /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
 [roofline] No roofline data found. Generating...
@@ -147,7 +147,7 @@ GPU Device 3: Profiling...
 To reduce verbosity of profiling output try the `--quiet` flag which will hide rocprofiler output and activate a progress bar.
 ```

-You will notice two main stages in *default* Omniperf profiling. 
+You will notice two main stages in *default* Omniperf profiling.

 1. The first stage collects all the counters needed for Omniperf analysis (omitting any filters you have provided).

@@ -158,7 +158,7 @@ In this document, we use the term System on Chip (SoC) to refer to a particular
  - "MI200" for the AMD Instinct (tm) MI200 family of accelerators
  - "MI100" for the AMD Instinct (tm) MI100 family of accelerators
  - etc.
-  
+
  The SoC names are generated as a part of Omniperf, and do not _always_ distinguish between different accelerators in the same family (e.g., an AMD Instinct (tm) MI210 vs an MI250)

 ```{note}
@@ -208,12 +208,12 @@ The following example only gathers hardware counters for the Shader Sequencer (S
 ```shell-session
 $ omniperf profile --name vcopy -b SQ TCC -- ./vcopy -n 1048576 -b 256

-  ___                  _                  __ 
+  ___                  _                  __
 / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
+| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
 | |_| | | | | | | | | | | |_) |  __/ |  |  _|
- \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                        |_|                  
+ \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
+                        |_|

 fname: pmc_cpc_perf: Skipped
 fname: pmc_spi_perf: Skipped
@@ -252,12 +252,12 @@ The following example demonstrates profiling isolating the kernel matching subst
 ```shell-session
 $ omniperf profile --name vcopy -k vecCopy -- ./vcopy -n 1048576 -b 256

-  ___                  _                  __ 
+  ___                  _                  __
 / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
+| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
 | |_| | | | | | | | | | | |_) |  __/ |  |  _|
- \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                        |_|                  
+ \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
+                        |_|

 Omniperf version: 2.0.0
 Profiler choice: rocprofv1
@@ -275,18 +275,18 @@ Collecting Performance Counters
 ```

 #### Dispatch Filtering
-Dispatch filtering is based on the *global* dispatch index of kernels in a run. 
+Dispatch filtering is based on the *global* dispatch index of kernels in a run.

 The following example profiles only the first kernel dispatch in execution of the application (please note zero-based indexing):
 ```shell-session
 $ omniperf profile --name vcopy -d 0 -- ./vcopy -n 1048576 -b 256

-  ___                  _                  __ 
+  ___                  _                  __
 / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
+| | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
 | |_| | | | | | | | | | | |_) |  __/ |  |  _|
- \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                        |_|                  
+ \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
+                        |_|

 Omniperf version: 2.0.0
 Profiler choice: rocprofv1
@@ -305,7 +305,7 @@ Collecting Performance Counters


 ### Standalone Roofline
-If you are only interested in generating roofline analysis data try using `--roof-only`. This will only collect counters relevant to roofline, as well as generate a standalone .pdf output of your roofline plot. 
+If you are only interested in generating roofline analysis data try using `--roof-only`. This will only collect counters relevant to roofline, as well as generate a standalone .pdf output of your roofline plot.

 Standalone Roofline Options:

@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf performance model: Command processor (CP)
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, command, processor, fetcher, packet processor, CPF, CPC
+   :description: ROCm Compute Profiler performance model: Command processor (CP)
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, command, processor, fetcher, packet processor, CPF, CPC

 **********************
 Command processor (CP)
@@ -9,7 +9,7 @@ Command processor (CP)
 The command processor (CP) is responsible for interacting with the AMDGPU kernel
 driver -- the Linux kernel -- on the CPU and for interacting with user-space
 HSA clients when they submit commands to HSA queues. Basic tasks of the CP
-include reading commands (such as, corresponding to a kernel launch) out of 
+include reading commands (such as, corresponding to a kernel launch) out of
 :hsa-runtime-pdf:`HSA queues <68>`, scheduling work to subsequent parts of the
 scheduler pipeline, and marking kernels complete for synchronization events on
 the host.
@@ -25,7 +25,7 @@ The command processor consists of two sub-components:
  scheduling.

 Before scheduling work to the accelerator, the command processor can
-first acquire a memory fence to ensure system consistency 
+first acquire a memory fence to ensure system consistency
 (:hsa-runtime-pdf:`Section 2.6.4 <91>`). After the work is complete, the
 command processor can apply a memory-release fence. Depending on the AMD CDNA™
 accelerator under question, either of these operations *might* initiate a cache
@@ -86,7 +86,7 @@ Command processor fetcher (CPF)
   * - CPF-UTCL1 Stall

     - Percent of CPF busy cycles where the CPF was stalled by address
-       translation. 
+       translation.

     - Percent

@@ -151,4 +151,3 @@ Command processor packet processor (CPC)
       work.

     - Percent
-
@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf performance model: Compute unit (CU)
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, GCN, compute, unit, pipeline, workgroup, wavefront,
+   :description: ROCm Compute Profiler performance model: Compute unit (CU)
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, GCN, compute, unit, pipeline, workgroup, wavefront,
              CDNA

 *****************
@@ -14,12 +14,12 @@ CDNA™-based accelerators. All :ref:`wavefronts <desc-wavefront>` of a
 .. image:: ../data/performance-model/gcn_compute_unit.png
   :align: center
   :alt: AMD CDNA accelerator compute unit diagram
-   :width: 800 
+   :width: 800

 The CU consists of several independent execution pipelines and functional units.
 The :doc:`/conceptual/pipeline-descriptions` section details the various
 execution pipelines -- VALU, SALU, LDS, scheduler, and so forth. The metrics
-presented by Omniperf for these pipelines are described in
+presented by ROCm Compute Profiler for these pipelines are described in
 :doc:`pipeline-metrics`. The :doc:`vL1D <vector-l1-cache>` cache and
 :doc:`LDS <local-data-share>` are described in their own sections.

@@ -57,4 +57,3 @@ presented by Omniperf for these pipelines are described in

 For a more in-depth description of a compute unit on a CDNA accelerator, see
 :hip-training-pdf:`22` and :gcn-crash-course:`27`.
-
@@ -1,13 +1,13 @@
 .. meta::
-   :description: Omniperf terminology and definitions
-   :keywords: Omniperf, ROCm, glossary, definitions, terms, profiler, tool,
+   :description: ROCm Compute Profiler terminology and definitions
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, glossary, definitions, terms, profiler, tool,
              Instinct, accelerator, AMD

 ***********
 Definitions
 ***********

-The following table briefly defines some terminology used in Omniperf interfaces
+The following table briefly defines some terminology used in ROCm Compute Profiler interfaces
 and in this documentation.

 .. include:: ./includes/terms.rst
@@ -34,7 +34,7 @@ include:
       that is, the total runtime of the kernel in seconds, as measured by the
       :doc:`command processor <command-processor>`.

-By default, Omniperf uses the ``per_wave`` normalization.
+By default, ROCm Compute Profiler uses the ``per_wave`` normalization.

 .. tip::

@@ -44,4 +44,3 @@ By default, Omniperf uses the ``per_wave`` normalization.
   (and what types) of instructions are used per wavefront. A ``per_kernel``
   normalization can be useful to get the total aggregate values of metrics for
   comparison between different configurations.
-
@@ -185,4 +185,3 @@
       branches of a conditional with different sets of work-items active.

     - N/A
-
@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf performance model: L2 cache (TCC)
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, L2, cache, infinity fabric, metrics
+   :description: ROCm Compute Profiler performance model: L2 cache (TCC)
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, L2, cache, infinity fabric, metrics

 **************
 L2 cache (TCC)
@@ -21,7 +21,7 @@ across the L2 channels. Requests that miss in the L2 cache are passed out to
 :ref:`Infinity Fabric™ <l2-fabric>` to be routed to the appropriate memory
 location.

-The L2 cache metrics reported by Omniperf are broken down into four
+The L2 cache metrics reported by ROCm Compute Profiler are broken down into four
 categories:

 *  :ref:`L2 Speed-of-Light <l2-sol>`
@@ -181,7 +181,7 @@ This section details the incoming requests to the L2 cache from the
     - The number of coherence probe requests made to the L2 cache from outside
       the accelerator. On an :ref:`MI2XX <mixxx-note>`, probe requests may be
       generated by, for example, writes to
-       :ref:`fine-grained device <memory-type>` memory or by writes to 
+       :ref:`fine-grained device <memory-type>` memory or by writes to
       :ref:`coarse-grained <memory-type>` device memory.

     - Requests per :ref:`normalization unit <normalization-units>`
@@ -299,7 +299,7 @@ accelerator’s memory, or even in the CPU’s memory. Infinity Fabric
 is responsible for routing these memory requests/data to the correct
 location and returning any fetched data to the L2 cache. The
 :ref:`l2-request-flow` describes the flow of these requests through
-Infinity Fabric in more detail, as described by Omniperf metrics,
+Infinity Fabric in more detail, as described by ROCm Compute Profiler metrics,
 while :ref:`l2-request-metrics` give detailed definitions of
 individual metrics.

@@ -309,7 +309,7 @@ Request flow
 ------------

 The following is a diagram that illustrates how L2↔Fabric requests are reported
-by Omniperf:
+by ROCm Compute Profiler:

 .. figure:: ../data/performance-model/fabric.png
   :align: center
@@ -773,4 +773,3 @@ remote accelerators or CPUs.
 .. rubric:: Disclaimer

 PCIe® is a registered trademark of PCI-SIG Corporation.
-
@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf performance model: Local data share (LDS)
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, local, data, share, LDS
+   :description: ROCm Compute Profiler performance model: Local data share (LDS)
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, local, data, share, LDS

 **********************
 Local data share (LDS)
@@ -180,4 +180,3 @@ The LDS statistics panel gives a more detailed view of the hardware:
       expected to be zero in most configurations for modern CDNA™ accelerators.

     - Accesses per :ref:`normalization unit <normalization-units>`
-
@@ -1,13 +1,13 @@
 .. meta::
-   :description: Omniperf performance model
-   :keywords: Omniperf, ROCm, performance, model, profiler, tool, Instinct,
+   :description: ROCm Compute Profiler performance model
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, performance, model, profiler, tool, Instinct,
              accelerator, AMD

 *****************
 Performance model
 *****************

-Omniperf makes available an extensive list of metrics to better understand
+ROCm Compute Profiler makes available an extensive list of metrics to better understand
 achieved application performance on AMD Instinct™ MI-series accelerators
 including Graphics Core Next™ (GCN) GPUs like the AMD Instinct MI50, CDNA™
 accelerators like the MI100, and CDNA2 accelerators such as the MI250X, MI250,
@@ -18,7 +18,7 @@ hardware blocks of AMD Instinct accelerators. This section describes each
 hardware block on the accelerator as interacted with by a software developer to
 give a deeper understanding of the metrics reported by profiling data. Refer to
 :doc:`/tutorial/profiling-by-example` for more practical examples and details on how
-to use Omniperf to optimize your code.
+to use ROCm Compute Profiler to optimize your code.

 .. _mixxx-note:

@@ -34,7 +34,7 @@ to use Omniperf to optimize your code.
   :prod-page:`MI250 <mi200/mi250>`, and :prod-page:`MI210 <mi200/mi210>`
   product pages.

-In this chapter, the AMD Instinct performance model used by Omniperf is divided into a handful of
+In this chapter, the AMD Instinct performance model used by ROCm Compute Profiler is divided into a handful of
 key hardware blocks, each detailed in the following sections:

 * :doc:`compute-unit`
@@ -46,4 +46,3 @@ key hardware blocks, each detailed in the following sections:
 * :doc:`command-processor`

 * :doc:`system-speed-of-light`
-
@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf performance model: Shader engine (SE)
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, pipeline, VALU, SALU, VMEM, SMEM, LDS, branch,
+   :description: ROCm Compute Profiler performance model: Shader engine (SE)
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, pipeline, VALU, SALU, VMEM, SMEM, LDS, branch,
              scheduler, MFMA, AGPRs

 *********************
@@ -101,7 +101,7 @@ coordinate between wavefronts in a workgroup.
   Performance model of the local data share (LDS) on AMD Instinct MI-series
   accelerators.

-Above is Omniperf's performance model of the LDS on CDNA accelerators (adapted
+Above is ROCm Compute Profiler's performance model of the LDS on CDNA accelerators (adapted
 from  :mantor-gcn-pdf:`20`). The SIMDs in the :ref:`VALU <desc-valu>` are
 connected to the LDS in pairs (see above). Only one SIMD per pair may issue an
 LDS instruction at a time, but both pairs may issue concurrently.
@@ -186,7 +186,7 @@ shadow (see the :ref:`MFMA <desc-mfma>` section for more detail).

 .. note::

-   The IPC model used by Omniperf omits the following two complications for
+   The IPC model used by ROCm Compute Profiler omits the following two complications for
   clarity. First, CDNA accelerators contain other execution units on the CU
   that are unused for compute applications. Second, so-called "internal"
   instructions (see :gcn-crash-course:`29`) are not issued to a functional
@@ -237,7 +237,7 @@ various AMD accelerators (including the CDNA line), we recommend the
            GPRs required for D: 4
            GPR alignment requirement: 8 bytes

-For the purposes of Omniperf, the MFMA unit is typically treated as a separate
+For the purposes of ROCm Compute Profiler, the MFMA unit is typically treated as a separate
 pipeline from the :ref:`VALU <desc-valu>`, as other VALU instructions (along
 with other execution pipelines such as the :ref:`SALU <desc-salu>`) typically can be
 issued during a portion of the total duration of an MFMA operation.
@@ -296,4 +296,3 @@ math accumulation VGPRs (AGPRs). The AMD Instinct :ref:`MI2XX <mixxx-note>`
 (CDNA2) has a 512 KiB VGPR file per CU, where each wave can dynamically request
 up to 256 KiB of VGPRs and an additional 256 KiB of AGPRs. For more information,
 refer to `this comment <https://github.com/ROCm/ROCm/issues/1689#issuecomment-1553751913>`_.
-
@@ -1,13 +1,13 @@
 .. meta::
-   :description: Omniperf performance model: Pipeline metrics
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, pipeline, wavefront, metrics, launch, runtime
+   :description: ROCm Compute Profiler performance model: Pipeline metrics
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, pipeline, wavefront, metrics, launch, runtime
              VALU, MFMA, instruction mix, FLOPs, arithmetic, operations

 ****************
 Pipeline metrics
 ****************

-In this section, we describe the metrics available in Omniperf to analyze the
+In this section, we describe the metrics available in ROCm Compute Profiler to analyze the
 pipelines discussed in the :doc:`pipeline-descriptions`.

 .. _wavefront:
@@ -233,7 +233,7 @@ Instruction mix

 The instruction mix panel shows a breakdown of the various types of instructions
 executed by the user’s kernel, and which pipelines on the
-:doc:`CU <compute-unit>` they were executed on. In addition, Omniperf reports
+:doc:`CU <compute-unit>` they were executed on. In addition, ROCm Compute Profiler reports
 further information about the breakdown of operation types for the
 :ref:`VALU <desc-valu>`, vector-memory, and :ref:`MFMA <desc-mfma>`
 instructions.
@@ -555,7 +555,7 @@ Compute pipeline
 FLOP counting conventions
 -------------------------

-Omniperf’s conventions for VALU FLOP counting are as follows:
+ROCm Compute Profiler’s conventions for VALU FLOP counting are as follows:

 * Addition or multiplication: 1 operation

@@ -906,4 +906,3 @@ not. For more detail on how operations are counted see the
       accelerators, the VALU has no native INT8 instructions.

     - IOPs per :ref:`normalization unit <normalization-units>`
-
@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf performance model: References
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, HIP, GCN, LLVM, docs, documentation, training
+   :description: ROCm Compute Profiler performance model: References
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, HIP, GCN, LLVM, docs, documentation, training

 **********
 References
@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf performance model: Shader engine (SE)
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, shader, engine, sL1D, L1I, workgroup manager, SPI
+   :description: ROCm Compute Profiler performance model: Shader engine (SE)
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, shader, engine, sL1D, L1I, workgroup manager, SPI

 ******************
 Shader engine (SE)
@@ -21,7 +21,7 @@ The number of CUs on a SE varies from chip to chip -- see for example
 :hip-training-pdf:`20`. In addition, newer accelerators such as the AMD
 Instinct™ MI 250X have 8 SEs per accelerator.

-For the purposes of Omniperf, we consider resources that are shared between
+For the purposes of ROCm Compute Profiler, we consider resources that are shared between
 multiple CUs on a single SE as part of the SE's metrics.

 These include:
@@ -487,7 +487,7 @@ issuing concurrently).

 .. note::

-   Current versions of the profiling libraries underlying Omniperf attempt to
+   Current versions of the profiling libraries underlying ROCm Compute Profiler attempt to
   serialize concurrent kernels running on the accelerator, as the performance
   counters on the device are global (that is, shared between concurrent
   kernels). This means that these scheduler-pipe utilization metrics are
@@ -704,4 +704,3 @@ such that improving occupancy further may not improve performance. See
       accelerators).

     - Percent
-
@@ -1,13 +1,13 @@
 .. meta::
-   :description: Omniperf performance model: System Speed-of-Light
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, system, speed of light
+   :description: ROCm Compute Profiler performance model: System Speed-of-Light
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, system, speed of light

 *********************
 System Speed-of-Light
 *********************

 System Speed-of-Light summarizes some of the key metrics from various sections
-of Omniperf’s profiling report.
+of ROCm Compute Profiler’s profiling report.

 .. warning::

@@ -315,4 +315,3 @@ of Omniperf’s profiling report.
       :doc:`CU <compute-unit>`.

     - Cycles
-
@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf performance model: Vector L1 cache (vL1D)
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, vector, l1, cache, vl1d
+   :description: ROCm Compute Profiler performance model: Vector L1 cache (vL1D)
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, vector, l1, cache, vl1d

 **********************
 Vector L1 cache (vL1D)
@@ -124,7 +124,7 @@ passes information about the commands (coalescing state, destination SIMD,
 etc.) to the :ref:`data processing unit <desc-td>` for use after the requested
 data has been retrieved.

-Omniperf reports several metrics to indicate performance bottlenecks in
+ROCm Compute Profiler reports several metrics to indicate performance bottlenecks in
 the address processing unit, which are broken down into a few
 categories:

@@ -378,7 +378,7 @@ Translation Cache (UTCL1). This cache contains a L1 Translation
 Lookaside Buffer (TLB) which stores recently translated addresses to
 reduce the cost of subsequent re-translations.

-Omniperf reports the following L1 TLB metrics:
+ROCm Compute Profiler reports the following L1 TLB metrics:

 .. list-table::
   :header-rows: 1
@@ -656,7 +656,7 @@ latencies of read/write memory operations to the :doc:`L2 cache <l2-cache>`.
   :ref:`Cache access metrics <vl1d-cache-stall-metrics>` section when
   evaluating the vL1D hit rate.

-.. [#vl1d-activity] Omniperf considers the vL1D to be active when any part of
+.. [#vl1d-activity] ROCm Compute Profiler considers the vL1D to be active when any part of
   the vL1D (excluding the :ref:`address processor <desc-ta>` and
   :ref:`data return <desc-td>` units) are active, for example, when performing
   a translation, waiting for data, accessing the Tag or Cache RAMs, etc.
@@ -685,7 +685,7 @@ from the :ref:`VALU <desc-valu>`. When data is returned from the
 :ref:`vL1D cache RAM <desc-tc>`, it is matched to this previously stored request
 data, and returned to the appropriate SIMD.

-Omniperf reports the following vL1D data-return path metrics:
+ROCm Compute Profiler reports the following vL1D data-return path metrics:

 .. list-table::
   :header-rows: 1
@@ -764,4 +764,3 @@ Omniperf reports the following vL1D data-return path metrics:
       :ref:`address processor <desc-ta>`.

     - Instructions per :ref:`normalization unit <normalization-units>`
-
@@ -35,7 +35,7 @@ with open("../VERSION", encoding="utf-8") as f:
    version_number = match[1]

 # project info
-project = "Omniperf"
+project = "ROCm Compute Profiler"
 author = "Advanced Micro Devices, Inc."
 copyright = "Copyright (c) 2024 Advanced Micro Devices, Inc. All rights reserved."
 version = version_number
@@ -51,11 +51,14 @@ html_static_path = ["sphinx/static/css"]
 html_css_files = ["o_custom.css"]

 external_toc_path = "./sphinx/_toc.yml"
-external_projects_current_project = "omniperf"
+external_projects_current_project = "rocprofiler-compute"

 # frequently used external resources
 extlinks = {
-    "dev-sample": ("https://github.com/ROCm/omniperf/blob/amd-mainline/sample/%s", "%s"),
+    "dev-sample": (
+        "https://github.com/ROCm/rocprofiler-compute/blob/amd-mainline/sample/%s",
+        "%s",
+    ),
    "prod-page": (
        "https://www.amd.com/en/products/accelerators/instinct/%s.html",
        "%s",
@@ -684,7 +684,7 @@
           y="240.85156"
           id="tspan43344"><tspan
             style="text-align:center;text-anchor:middle"
-             id="tspan43342">Atomic 
+             id="tspan43342">Atomic
 </tspan></tspan><tspan
           x="134.80859"
           y="260.85156"
@@ -1,14 +1,14 @@
 .. meta::
-   :description: Omniperf analysis: CLI analysis
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, command line, analyze, filtering, metrics, baseline, comparison
+   :description: ROCm Compute Profiler analysis: CLI analysis
+   :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, command line, analyze, filtering, metrics, baseline, comparison

 ************
 CLI analysis
 ************

-This section provides an overview of Omniperf's CLI analysis features.
+This section provides an overview of ROCm Compute Profiler's CLI analysis features.

-* :ref:`Derived metrics <cli-list-metrics>`: All of Omniperf's built-in metrics.
+* :ref:`Derived metrics <cli-list-metrics>`: All of ROCm Compute Profiler's built-in metrics.

 * :ref:`Baseline comparison <analysis-baseline-comparison>`: Compare multiple
  runs in a side-by-side manner.
@@ -19,28 +19,28 @@ This section provides an overview of Omniperf's CLI analysis features.
 * :ref:`Filtering <cli-analysis-options>`: Hone in on a particular kernel,
  GPU ID, or dispatch ID via post-process filtering.

-Run ``omniperf analyze -h`` for more details.
+Run ``rocprof-compute analyze -h`` for more details.

 .. _cli-walkthrough:

 Walkthrough
 ===========

-1. To begin, generate a high-level analysis report using Omniperf's ``-b`` (or ``--block``) flag. 
+1. To begin, generate a high-level analysis report using ROCm Compute Profiler's ``-b`` (or ``--block``) flag.

-   .. code-block:: shell
+   .. code-block:: shell-session

-      $ omniperf analyze -p workloads/vcopy/MI200/ -b 2
+      $ rocprof-compute analyze -p workloads/vcopy/MI200/ -b 2

-        ___                  _                  __ 
-       / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-      | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
-      | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-       \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                              |_|                  
+                                       __                                       _
+       _ __ ___   ___ _ __  _ __ ___  / _|       ___ ___  _ __ ___  _ __  _   _| |_ ___
+      | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \
+      | | | (_) | (__| |_) | | | (_) |  _|_____| (_| (_) | | | | | | |_) | |_| | ||  __/
+      |_|  \___/ \___| .__/|_|  \___/|_|        \___\___/|_| |_| |_| .__/ \__,_|\__\___|
+                     |_|                                           |_|

      Analysis mode = cli
-      [analysis] deriving Omniperf metrics...
+      [analysis] deriving rocprofiler-compute metrics...

      --------------------------------------------------------------------------------
      0. Top Stats
@@ -134,19 +134,19 @@ Walkthrough

 2. Use ``--list-metrics`` to generate a list of available metrics for inspection.

-   .. code-block:: shell
+   .. code-block:: shell-session

-      $ omniperf analyze -p workloads/vcopy/MI200/ --list-metrics gfx90a
+      $ rocprof-compute analyze -p workloads/vcopy/MI200/ --list-metrics gfx90a

-        ___                  _                  __ 
-       / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-      | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
-      | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-       \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                              |_|                  
+                                       __                                       _
+       _ __ ___   ___ _ __  _ __ ___  / _|       ___ ___  _ __ ___  _ __  _   _| |_ ___
+      | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \
+      | | | (_) | (__| |_) | | | (_) |  _|_____| (_| (_) | | | | | | |_) | |_| | ||  __/
+      |_|  \___/ \___| .__/|_|  \___/|_|        \___\___/|_| |_| |_| .__/ \__,_|\__\___|
+                     |_|                                           |_|

      Analysis mode = cli
-      [analysis] deriving Omniperf metrics...
+      [analysis] deriving rocprofiler-compute metrics...
      0 -> Top Stats
      1 -> System Info
      2 -> System Speed-of-Light
@@ -186,13 +186,13 @@ Walkthrough

 3. Choose your own customized subset of metrics with the ``-b`` (or ``--block``)
   option. Or, build your own configuration following
-   `config_template <https://github.com/ROCm/omniperf/blob/amd-mainline/src/rocprof_compute_soc/analysis_configs/panel_config_template.yaml>`_.
+   `config_template <https://github.com/ROCm/rocprofiler-compute/blob/amd-mainline/src/rocprof_compute_soc/analysis_configs/panel_config_template.yaml>`_.
   The following snippet shows how to generate a report containing only metric 2
   (:doc:`System Speed-of-Light </conceptual/system-speed-of-light>`).

-   .. code-block:: shell
+   .. code-block:: shell-session

-      $ omniperf analyze -p workloads/vcopy/MI200/ -b 2
+      $ rocprof-compute analyze -p workloads/vcopy/MI200/ -b 2

      --------
      Analyze
@@ -280,7 +280,7 @@ Walkthrough
 4. Optimize the application, iterate, and re-profile to inspect performance
   changes.

-5. Redo a comprehensive analysis with Omniperf CLI at any optimization
+5. Redo a comprehensive analysis with ROCm Compute Profiler CLI at any optimization
   milestone.

 .. _cli-analysis-options:
@@ -291,22 +291,22 @@ More analysis options
 Single run
  .. code-block:: shell

-     $ omniperf analyze -p workloads/vcopy/MI200/
+     $ rocprof-compute analyze -p workloads/vcopy/MI200/

 List top kernels and dispatches
  .. code-block:: shell

-     $ omniperf analyze -p workloads/vcopy/MI200/  --list-stats
+     $ rocprof-compute analyze -p workloads/vcopy/MI200/  --list-stats

 List metrics
  .. code-block:: shell

-     $ omniperf analyze -p workloads/vcopy/MI200/  --list-metrics gfx90a
+     $ rocprof-compute analyze -p workloads/vcopy/MI200/  --list-metrics gfx90a

 Show System Speed-of-Light and CS_Busy blocks only
  .. code-block:: shell

-     $ omniperf analyze -p workloads/vcopy/MI200/  -b 2  5.1.0
+     $ rocprof-compute analyze -p workloads/vcopy/MI200/  -b 2  5.1.0

 .. note::

@@ -319,10 +319,10 @@ Filter kernels

  .. code-block::

-     $ omniperf analyze -p workloads/vcopy/MI200/ --list-stats
+     $ rocprof-compute analyze -p workloads/vcopy/MI200/ --list-stats

     Analysis mode = cli
-     [analysis] deriving Omniperf metrics...
+     [analysis] deriving rocprofiler-compute metrics...

     --------------------------------------------------------------------------------
     Detected Kernels (sorted descending by duration)
@@ -344,12 +344,12 @@ Filter kernels
  ``vecCopy(double*, double*, double*, int, int) [clone .kd]`` at index ``0``.
  Then, use this index to apply the filter via ``-k`` or ``--kernels``.

-  .. code-block:: shell
+  .. code-block:: shell-session

-     $ omniperf analyze -p workloads/vcopy/MI200/ -k 0
+     $ rocprof-compute analyze -p workloads/vcopy/MI200/ -k 0

     Analysis mode = cli
-     [analysis] deriving Omniperf metrics...
+     [analysis] deriving rocprofiler-compute metrics...

     --------------------------------------------------------------------------------
     0. Top Stats
@@ -369,10 +369,10 @@ Filter kernels
 Baseline comparison
  .. code-block:: shell

-     omniperf analyze -p workload1/path/  -p workload2/path/
+     rocprof-compute analyze -p workload1/path/  -p workload2/path/

  OR

  .. code-block:: shell

-     omniperf analyze -p workload1/path/ -k 0  -p workload2/path/ -k 1
+     rocprof-compute analyze -p workload1/path/ -k 0  -p workload2/path/ -k 1
@@ -1,6 +1,7 @@
 .. meta::
-   :description: Omniperf analysis: Grafana GUI
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, Grafana, panels, GUI, import
+   :description: ROCm Compute Profiler analysis: Grafana GUI
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool,
+              Instinct, accelerator, Grafana, panels, GUI, import

 ********************
 Grafana GUI analysis
@@ -8,7 +9,7 @@ Grafana GUI analysis

 Find setup instructions in :doc:`../../install/grafana-setup`.

-The Omniperf Grafana analysis dashboard GUI supports the following features to
+The ROCm Compute Profiler Grafana analysis dashboard GUI supports the following features to
 facilitate MI accelerator performance profiling and analysis:

 * System and hardware component (hardware block)
@@ -40,7 +41,7 @@ facilitate MI accelerator performance profiling and analysis:

  * L2 Cache (TCC) (both aggregated and per-channel perf info)

-See the full list of :ref:`Omniperf's analysis panels <panels>`.
+See the full list of :ref:`ROCm Compute Profiler's analysis panels <panels>`.

 .. _analysis-sol:

@@ -70,14 +71,14 @@ normalizations are available.

 * ``per_second``

-See :ref:`normalization-units` to learn more about Omniperf normalizations.
+See :ref:`normalization-units` to learn more about ROCm Compute Profiler normalizations.

 .. _analysis-baseline-comparison:

 Baseline comparison
 -------------------

-Omniperf enables baseline comparison to allow checking A/B effect. Currently
+ROCm Compute Profiler enables baseline comparison to allow checking A/B effect. Currently
 baseline comparison is limited to the same :ref:`SoC <def-soc>`. Cross
 comparison between SoCs is in development.

@@ -92,14 +93,14 @@ setup the following filters to allow fine grained comparisons:

 * Dispatch ID filtering (regex filtering)

-* Omniperf Panels (multi-selection)
+* ROCm Compute Profiler Panels (multi-selection)

 .. _analysis-regex-dispatch-id:

 Regex-based dispatch ID filtering
 ---------------------------------

-Omniperf allows filtering via Regular Expressions (regex), a standard Linux
+ROCm Compute Profiler allows filtering via Regular Expressions (regex), a standard Linux
 string matching syntax, based dispatch ID filtering to flexibly choose the
 kernel invocations.

@@ -116,7 +117,7 @@ corresponding regex is : ``(1[7-9]|[23]\d|4[0-8])``.
 Incremental profiling
 ---------------------

-Omniperf supports incremental profiling to speed up performance analysis.
+ROCm Compute Profiler supports incremental profiling to speed up performance analysis.

 Refer to the :ref:`profiling-hw-component-filtering` section for this command.

@@ -145,7 +146,7 @@ Global variables and configurations

 .. image:: ../../data/analyze/global_variables.png
   :align: center
-   :alt: Omniperf global variables and configurations
+   :alt: ROCm Compute Profiler global variables and configurations
   :width: 800

 .. _grafana-gui-import:
@@ -153,7 +154,7 @@ Global variables and configurations
 Grafana GUI import
 ------------------

-The Omniperf database ``--import`` option imports the raw profiling data to
+The ROCm Compute Profiler database ``--import`` option imports the raw profiling data to
 Grafana's backend MongoDB database. This step is only required for Grafana
 GUI-based performance analysis.

@@ -169,13 +170,13 @@ convention:

 .. code-block:: shell

-    omniperf_<team>_<database>_<soc>
+   rocprofiler-compute_<team>_<database>_<soc>

 For example:

 .. code-block:: shell

-   omniperf_asw_vcopy_mi200
+   rocprofiler-compute_asw_vcopy_mi200

 When using :ref:`database mode <modes-database>`, be sure to tailor the
 connection options to the machine hosting your
@@ -187,10 +188,10 @@ called ``dummybox``.

 .. code-block:: shell-session

-   $ omniperf database --help
+   $ rocprof-compute database --help
   usage:

-   omniperf database <interaction type> [connection options]
+   rocprof-compute database <interaction type> [connection options]



@@ -198,9 +199,9 @@ called ``dummybox``.

   Examples:

-           omniperf database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/
+           rocprof-compute database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/

-           omniperf database --remove -H pavii1 -u temp -w omniperf_asw_sample_mi200
+           rocprof-compute database --remove -H pavii1 -u temp -w rocprofiler-compute_asw_sample_mi200

   -------------------------------------------------------------------------------

@@ -215,8 +216,8 @@ called ``dummybox``.
     -s, --specs        Print system specs.

   Interaction Type:
-     -i, --import                                  Import workload to Omniperf DB
-     -r, --remove                                  Remove a workload from Omniperf DB
+     -i, --import                                  Import workload to ROCm Compute Profiler DB
+     -r, --remove                                  Remove a workload from ROCm Compute Profiler DB

   Connection Options:
     -H , --host                                   Name or IP address of the server host.
@@ -228,22 +229,22 @@ called ``dummybox``.
     --kernel-verbose              Specify Kernel Name verbose level 1-5. Lower the level, shorter the kernel name. (DEFAULT: 5) (DISABLE: 5)


-Omniperf import for vcopy:
-^^^^^^^^^^^^^^^^^^^^^^^^^^
+ROCm Compute Profiler import for vcopy:
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

-.. code-block:: shell
+.. code-block:: shell-session

-   $ omniperf database --import -H dummybox -u temp -t asw -w workloads/vcopy/mi200/
+   $ rocprof-compute database --import -H dummybox -u temp -t asw -w workloads/vcopy/mi200/

-     ___                  _                  __
-    / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-   | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_
-   | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-    \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|
-                           |_|
+                                    __                                       _
+    _ __ ___   ___ _ __  _ __ ___  / _|       ___ ___  _ __ ___  _ __  _   _| |_ ___
+   | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \
+   | | | (_) | (__| |_) | | | (_) |  _|_____| (_| (_) | | | | | | |_) | |_| | ||  __/
+   |_|  \___/ \___| .__/|_|  \___/|_|        \___\___/|_| |_| |_| .__/ \__,_|\__\___|
+                  |_|                                           |_|


-   Pulling data from  /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
+   Pulling data from  /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200
   The directory exists
   Found sysinfo file
   KernelName shortening enabled
@@ -251,15 +252,15 @@ Omniperf import for vcopy:
   Password:
   Password received
   -- Conversion & Upload in Progress --
-     0%|                                                                                                                                                                                                             | 0/11 [00:00<?, ?it/s]/home/auser/repos/omniperf/sample/workloads/vcopy/MI200/SQ_IFETCH_LEVEL.csv
-     9%|█████████████████▉                                                                                                                                                                                   | 1/11 [00:00<00:01,  8.53it/s]/home/auser/repos/omniperf/sample/workloads/vcopy/MI200/pmc_perf.csv
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+    82%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                                   | 9/11 [00:00<00:00, 12.60it/s]/home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/timestamps.csv
   100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 11/11 [00:00<00:00, 11.05it/s]
   9 collections added.
   Workload name uploaded
@@ -267,8 +268,8 @@ Omniperf import for vcopy:

 .. _panels:

-Omniperf panels
---------------
+ROCm Compute Profiler panels
+----------------------------

 There are currently 18 main panel categories available for analyzing the compute
 workload performance. Each category contains several panels for close inspection
@@ -446,7 +447,7 @@ Kernel Time Histogram

 .. figure:: ../../data/analyze/grafana/Kernel_time_histogram.png
   :align: center
-   :alt: Kernel time histogram panel in Omniperf Grafana
+   :alt: Kernel time histogram panel in ROCm Compute Profiler Grafana
   :width: 800

   Mapping application kernel launches to execution duration.
@@ -456,7 +457,7 @@ Top Bottleneck Kernels

 .. figure:: ../../data/analyze/grafana/top-stat_panel.png
   :align: center
-   :alt: Top bottleneck kernels panel in Omniperf Grafana
+   :alt: Top bottleneck kernels panel in ROCm Compute Profiler Grafana
   :width: 800

   Top N kernels and relevant statistics. Sorted by total duration.
@@ -466,7 +467,7 @@ Top Bottleneck Dispatches

 .. figure:: ../../data/analyze/grafana/Top_bottleneck_dispatches.png
   :align: center
-   :alt: Top bottleneck dispatches panel in Omniperf Grafana
+   :alt: Top bottleneck dispatches panel in ROCm Compute Profiler Grafana
   :width: 800

   Top N kernel dispatches and relevant statistics. Sorted by total duration.
@@ -476,7 +477,7 @@ Current and Baseline Dispatch IDs (Filtered)

 .. figure:: ../../data/analyze/grafana/Current_and_baseline_dispatch_ids.png
   :align: center
-   :alt: Current and baseline dispatch IDs panel in Omniperf Grafana
+   :alt: Current and baseline dispatch IDs panel in ROCm Compute Profiler Grafana
   :width: 800

   List of all kernel dispatches.
@@ -488,10 +489,10 @@ System Speed-of-Light

 .. figure:: ../../data/analyze/grafana/sol_panel.png
   :align: center
-   :alt: System Speed-of-Light panel in Omniperf Grafana
+   :alt: System Speed-of-Light panel in ROCm Compute Profiler Grafana
   :width: 800

-   Key metrics from various sections of Omniperf’s profiling report.
+   Key metrics from various sections of ROCm Compute Profiler’s profiling report.

 .. tip::

@@ -510,7 +511,7 @@ Memory Chart Analysis

 .. figure:: ../../data/analyze/grafana/memory-chart_panel.png
   :align: center
-   :alt: Memory Chart Analysis panel in Omniperf Grafana
+   :alt: Memory Chart Analysis panel in ROCm Compute Profiler Grafana
   :width: 800

   A graphical representation of performance data for memory blocks on the GPU.
@@ -523,7 +524,7 @@ Empirical Roofline Analysis

 .. figure:: ../../data/analyze/grafana/roofline_panel.png
   :align: center
-   :alt: Roofline Analysis panel in Omniperf Grafana
+   :alt: Roofline Analysis panel in ROCm Compute Profiler Grafana
   :width: 800

   Visualize achieved performance relative to a benchmarked peak performance.
@@ -543,7 +544,7 @@ Command Processor Fetcher

 .. figure:: ../../data/analyze/grafana/cpc_panel.png
   :align: center
-   :alt: Command Processor Fetcher panel in Omniperf Grafana
+   :alt: Command Processor Fetcher panel in ROCm Compute Profiler Grafana
   :width: 800

   Fetches commands out of memory to hand them over to the Command Processor
@@ -554,7 +555,7 @@ Command Processor Compute

 .. figure:: ../../data/analyze/grafana/cpf_panel.png
   :align: center
-   :alt: Command Processor Compute panel in Omniperf Grafana
+   :alt: Command Processor Compute panel in ROCm Compute Profiler Grafana
   :width: 800

   The micro-controller running the command processing firmware that decodes the
@@ -575,7 +576,7 @@ SPI Stats

 .. figure:: ../../data/analyze/grafana/spi-stats_panel.png
   :align: center
-   :alt: SPI Stats panel in Omniperf Grafana
+   :alt: SPI Stats panel in ROCm Compute Profiler Grafana
   :width: 800

 ..
@@ -586,7 +587,7 @@ SPI Resource Allocation

 .. figure:: ../../data/analyze/grafana/spi-resource-allocation_panel.png
   :align: center
-   :alt: SPI Resource Allocation panel in Omniperf Grafana
+   :alt: SPI Resource Allocation panel in ROCm Compute Profiler Grafana
   :width: 800

 ..
@@ -602,7 +603,7 @@ Wavefront Launch Stats

 .. figure:: ../../data/analyze/grafana/wavefront-launch-stats_panel.png
   :align: center
-   :alt: Wavefront Launch Stats panel in Omniperf Grafana
+   :alt: Wavefront Launch Stats panel in ROCm Compute Profiler Grafana
   :width: 800

   General information about the kernel launch.
@@ -616,7 +617,7 @@ Wavefront Runtime Stats

 .. figure:: ../../data/analyze/grafana/wavefront-runtime-stats_panel.png
   :align: center
-   :alt: Wavefront Runtime Stats panel in Omniperf Grafana.
+   :alt: Wavefront Runtime Stats panel in ROCm Compute Profiler Grafana.
   :width: 800

   High-level overview of the execution of wavefronts in a kernel.
@@ -635,7 +636,7 @@ Instruction Mix

 .. figure:: ../../data/analyze/grafana/cu-inst-mix_panel.png
   :align: center
-   :alt: Instruction Mix panel in Omniperf Grafana
+   :alt: Instruction Mix panel in ROCm Compute Profiler Grafana
   :width: 800

   Breakdown of the various types of instructions executed by the user’s kernel,
@@ -650,7 +651,7 @@ VALU Arithmetic Instruction Mix

 .. figure:: ../../data/analyze/grafana/cu-value-arith-instr-mix_panel.png
   :align: center
-   :alt: VALU Arithmetic Instruction Mix panel in Omniperf Grafana
+   :alt: VALU Arithmetic Instruction Mix panel in ROCm Compute Profiler Grafana
   :width: 800

   The various types of vector instructions that were issued to the vector
@@ -665,7 +666,7 @@ MFMA Arithmetic Instruction Mix

 .. figure:: ../../data/analyze/grafana/cu-mafma-arith-instr-mix_panel.png
   :align: center
-   :alt: MFMA Arithmetic Instruction Mix panel in Omniperf Grafana
+   :alt: MFMA Arithmetic Instruction Mix panel in ROCm Compute Profiler Grafana
   :width: 800

   The types of Matrix Fused Multiply-Add (MFMA) instructions that were issued.
@@ -679,7 +680,7 @@ VMEM Arithmetic Instruction Mix

 .. figure:: ../../data/analyze/grafana/cu-vmem-instr-mix_panel.png
   :align: center
-   :alt: VMEM Arithmetic Instruction Mix panel in Omniperf Grafana
+   :alt: VMEM Arithmetic Instruction Mix panel in ROCm Compute Profiler Grafana
   :width: 800

   The types of vector memory (VMEM) instructions that were issued.
@@ -698,7 +699,7 @@ Speed-of-Light

 .. figure:: ../../data/analyze/grafana/cu-sol_panel.png
   :align: center
-   :alt: Speed-of-Light (CU) panel in Omniperf Grafana
+   :alt: Speed-of-Light (CU) panel in ROCm Compute Profiler Grafana
   :width: 800

   The number of floating-point and integer operations executed on the vector
@@ -714,7 +715,7 @@ Pipeline Stats

 .. figure:: ../../data/analyze/grafana/cu-pipeline-stats_panel.png
   :align: center
-   :alt: Pipeline Stats panel in Omniperf Grafana
+   :alt: Pipeline Stats panel in ROCm Compute Profiler Grafana
   :width: 800

   More detailed metrics to analyze the several independent pipelines found in
@@ -729,7 +730,7 @@ Arithmetic Operations

 .. figure:: ../../data/analyze/grafana/cu-arith-ops_panel.png
   :align: center
-   :alt: Arithmetic Operations panel in Omniperf Grafana
+   :alt: Arithmetic Operations panel in ROCm Compute Profiler Grafana
   :width: 800

   The total number of floating-point and integer operations executed in various
@@ -749,7 +750,7 @@ Speed-of-Light

 .. figure:: ../../data/analyze/grafana/lds-sol_panel.png
   :align: center
-   :alt: Speed-of-Light (LDS) panel in Omniperf Grafana
+   :alt: Speed-of-Light (LDS) panel in ROCm Compute Profiler Grafana
   :width: 800

   Key metrics for the Local Data Share (LDS) as a comparison with the peak
@@ -764,7 +765,7 @@ LDS Stats

 .. figure:: ../../data/analyze/grafana/lds-stats_panel.png
   :align: center
-   :alt: LDS Stats panel in Omniperf Grafana
+   :alt: LDS Stats panel in ROCm Compute Profiler Grafana
   :width: 800

   More detailed view of the Local Data Share (LDS) performance.
@@ -783,7 +784,7 @@ Speed-of-Light

 .. figure:: ../../data/analyze/grafana/instr-cache-sol_panel.png
   :align: center
-   :alt: Speed-of-Light (instruction cache) panel in Omniperf Grafana
+   :alt: Speed-of-Light (instruction cache) panel in ROCm Compute Profiler Grafana
   :width: 800

   Key metrics of the L1 Instruction (L1I) cache as a comparison with the peak
@@ -798,7 +799,7 @@ Instruction Cache Stats

 .. figure:: ../../data/analyze/grafana/instr-cache-accesses_panel.png
   :align: center
-   :alt: Instruction Cache Stats panel in Omniperf Grafana
+   :alt: Instruction Cache Stats panel in ROCm Compute Profiler Grafana
   :width: 800

   More detail on the hit/miss statistics of the L1 Instruction (L1I) cache.
@@ -821,7 +822,7 @@ Speed-of-Light

 .. figure:: ../../data/analyze/grafana/sl1d-sol_panel.png
   :align: center
-   :alt: Speed-of-Light (SL1D) panel in Omniperf Grafana
+   :alt: Speed-of-Light (SL1D) panel in ROCm Compute Profiler Grafana
   :width: 800

   Key metrics of the Scalar L1 Data (sL1D) cache as a comparison with the peak
@@ -836,7 +837,7 @@ Scalar L1D Cache Accesses

 .. figure:: ../../data/analyze/grafana/sl1d-cache-accesses_panel.png
   :align: center
-   :alt: Scalar L1D Cache Accesses panel in Omniperf Grafana
+   :alt: Scalar L1D Cache Accesses panel in ROCm Compute Profiler Grafana
   :width: 800

   More detail on the types of accesses made to the Scalar L1 Data (sL1D) cache,
@@ -851,7 +852,7 @@ Scalar L1D Cache - L2 Interface

 .. figure:: ../../data/analyze/grafana/sl1d-l12-interface_panel.png
   :align: center
-   :alt: Scalar L1D Cache - L2 Interface panel in Omniperf Grafana
+   :alt: Scalar L1D Cache - L2 Interface panel in ROCm Compute Profiler Grafana
   :width: 800

   More detail on the data requested across the Scalar L1 Data (sL1D) cache <->
@@ -871,7 +872,7 @@ Texture Addresser

 .. figure:: ../../data/analyze/grafana/ta_panel.png
   :align: center
-   :alt: Texture Addresser in Omniperf Grafana
+   :alt: Texture Addresser in ROCm Compute Profiler Grafana
   :width: 800

   Metric specific to texture addresser (TA) which receives commands (e.g.,
@@ -889,7 +890,7 @@ Texture Data

 .. figure:: ../../data/analyze/grafana/td_panel.png
   :align: center
-   :alt: Texture Data panel in Omniperf Grafana
+   :alt: Texture Data panel in ROCm Compute Profiler Grafana
   :width: 800

   Metrics specific to texture data (TD) which routes data back to the
@@ -909,7 +910,7 @@ Speed-of-Light

 .. figure:: ../../data/analyze/grafana/vl1d-sol_panel.png
   :align: center
-   :alt: Speed-of-Light (VL1D) panel in Omniperf Grafana
+   :alt: Speed-of-Light (VL1D) panel in ROCm Compute Profiler Grafana
   :width: 800

   Key metrics of the vector L1 data (vL1D) cache as a comparison with the peak
@@ -924,7 +925,7 @@ L1D Cache Stalls

 .. figure:: ../../data/analyze/grafana/vl1d-cache-stalls_panel.png
   :align: center
-   :alt: L1D Cache Stalls panel in Omniperf Grafana
+   :alt: L1D Cache Stalls panel in ROCm Compute Profiler Grafana
   :width: 800

   More detail on where vector L1 data (vL1D) cache is stalled in the pipeline,
@@ -955,7 +956,7 @@ L1D - L2 Transactions

 .. figure:: ../../data/analyze/grafana/vl1d-l2-transactions_panel.png
   :align: center
-   :alt: L1D - L2 Transactions in Omniperf Grafana
+   :alt: L1D - L2 Transactions in ROCm Compute Profiler Grafana
   :width: 800

   A more granular look at the types of requests made to the L2 cache.
@@ -969,7 +970,7 @@ L1D Addr Translation

 .. figure:: ../../data/analyze/grafana/vl1d-addr-translation_panel.png
   :align: center
-   :alt: L1D Addr Translation panel in Omniperf Grafana
+   :alt: L1D Addr Translation panel in ROCm Compute Profiler Grafana
   :width: 800

   After a vector memory instruction has been processed/coalesced by the address
@@ -995,7 +996,7 @@ Speed-of-Light

 .. figure:: ../../data/analyze/grafana/l2-sol_panel.png
   :align: center
-   :alt: Speed-of-Light (L2 cache) panel in Omniperf Grafana
+   :alt: Speed-of-Light (L2 cache) panel in ROCm Compute Profiler Grafana
   :width: 800

   Key metrics about the performance of the L2 cache, aggregated over all the
@@ -1011,7 +1012,7 @@ L2 Cache Accesses

 .. figure:: ../../data/analyze/grafana/l2-accesses_panel.png
   :align: center
-   :alt: L2 Cache Accesses panel in Omniperf Grafana
+   :alt: L2 Cache Accesses panel in ROCm Compute Profiler Grafana
   :width: 800

   Incoming requests to the L2 cache from the vector L1 data (vL1D) cache and
@@ -1026,7 +1027,7 @@ L2 - Fabric Transactions

 .. figure:: ../../data/analyze/grafana/l2-fabric-transactions_panel.png
   :align: center
-   :alt: L2 - Fabric Transactions panel in Omniperf Grafana
+   :alt: L2 - Fabric Transactions panel in ROCm Compute Profiler Grafana
   :width: 800

   More detail on the flow of requests through Infinity Fabric™.
@@ -1040,7 +1041,7 @@ L2 - Fabric Interface Stalls

 .. figure:: ../../data/analyze/grafana/l2-fabric-interface-stalls_panel.png
   :align: center
-   :alt: L2 - Fabric Interface Stalls panel in Omniperf Grafana
+   :alt: L2 - Fabric Interface Stalls panel in ROCm Compute Profiler Grafana
   :width: 800

   A breakdown of what types of requests in a kernel caused a stall
@@ -1065,7 +1066,7 @@ Aggregate Stats

 .. figure:: ../../data/analyze/grafana/l2-per-channel-agg-stats_panel.png
   :align: center
-   :alt: Aggregate Stats (L2 cache per channel) panel in Omniperf Grafana
+   :alt: Aggregate Stats (L2 cache per channel) panel in ROCm Compute Profiler Grafana
   :width: 800

   L2 Cache per channel performance at a glance. Metrics are aggregated over all available channels.
@@ -1,22 +1,22 @@
 .. meta::
-   :description: How to use Omniperf's analyze mode
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD,
+   :description: How to use ROCm Compute Profiler's analyze mode
+   :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD,
              Grafana, analysis, analyze mode

 ************
 Analyze mode
 ************

-Omniperf offers several ways to interact with the metrics it generates from
+ROCm Compute Profiler offers several ways to interact with the metrics it generates from
 profiling. Your level of familiarity with the profiled application, computing
-environment, and experience with Omniperf should inform the analysis method you
+environment, and experience with ROCm Compute Profiler should inform the analysis method you
 choose.

-While analyzing with the CLI offers quick and straightforward access to Omniperf
+While analyzing with the CLI offers quick and straightforward access to ROCm Compute Profiler
 metrics from the terminal, Grafana's dashboard GUI adds an extra layer of
 readability and interactivity you might prefer.

-See the following sections to explore Omniperf's analysis and visualization
+See the following sections to explore ROCm Compute Profiler's analysis and visualization
 options.

 * :doc:`cli`
@@ -32,5 +32,5 @@ options.
   Unless otherwise noted, the performance analysis is done on the
   :ref:`MI200 platform <def-soc>`.

-Learn about profiling with Omniperf in :doc:`../profile/mode`. For an overview of
-Omniperf's other modes, see :ref:`modes`.
+Learn about profiling with ROCm Compute Profiler in :doc:`../profile/mode`. For an overview of
+ROCm Compute Profiler's other modes, see :ref:`modes`.
@@ -1,15 +1,15 @@
 .. meta::
-   :description: Omniperf analysis: Standalone GUI
+   :description: ROCm Compute Profiler analysis: Standalone GUI
   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, GUI, standalone, filter

 ***********************
 Standalone GUI analysis
 ***********************

-Omniperf's standalone analysis GUI is a lightweight web page that you can
+ROCm Compute Profiler's standalone analysis GUI is a lightweight web page that you can
 generate straight from the command line. The standalone analysis GUI is an
 alternative to the CLI if you want to explore profiling results visually, but
-without the additional setup requirements or server-side overhead of Omniperf's
+without the additional setup requirements or server-side overhead of ROCm Compute Profiler's
 detailed :doc:`Grafana interface <grafana-gui>` option. This analysis
 option is implemented as a simple `Flask <https://flask.palletsprojects.com>`_
 application that lets you view results from your preferred web browser.
@@ -29,22 +29,22 @@ application that lets you view results from your preferred web browser.
 Launch the standalone GUI analyzer
 ----------------------------------

-To launch the Omniperf GUI analyzer, include the ``--gui`` flag with your
+To launch the ROCm Compute Profiler GUI analyzer, include the ``--gui`` flag with your
 desired analysis command. For example:

-.. code-block:: shell
+.. code-block:: shell-session

-   $ omniperf analyze -p workloads/vcopy/MI200/ --gui
+   $ rocprof-compute analyze -p workloads/vcopy/MI200/ --gui

-     ___                  _                  __ 
-    / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-   | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
-   | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-    \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                           |_|                  
+                                    __                                       _
+    _ __ ___   ___ _ __  _ __ ___  / _|       ___ ___  _ __ ___  _ __  _   _| |_ ___
+   | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \
+   | | | (_) | (__| |_) | | | (_) |  _|_____| (_| (_) | | | | | | |_) | |_| | ||  __/
+   |_|  \___/ \___| .__/|_|  \___/|_|        \___\___/|_| |_| |_| .__/ \__,_|\__\___|
+                  |_|                                           |_|

   Analysis mode = web_ui
-   [analysis] deriving Omniperf metrics...
+   [analysis] deriving rocprofiler-compute metrics...
   Dash is running on http://0.0.0.0:8050/

    * Serving Flask app 'rocprof_compute_analyze.analysis_webui' (lazy loading)
@@ -62,7 +62,7 @@ At this point, you can launch your web browser of choice and navigate to

 .. image:: ../../data/analyze/standalone_gui.png
   :align: center
-   :alt: Omniperf standalone GUI home screen
+   :alt: ROCm Compute Profiler standalone GUI home screen
   :width: 800

 .. tip::
@@ -85,5 +85,5 @@ metrics specific to your selected filters.

 Once a filter is applied, you'll see several additional sections become
 available with detailed metrics specific to that area of AMD hardware. These
-detailed sections mirror the data displayed in Omniperf's
+detailed sections mirror the data displayed in ROCm Compute Profiler's
 :doc:`Grafana interface <grafana-gui>`.
@@ -1,27 +1,27 @@
 .. meta::
-   :description: How to use Omniperf's profile mode
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD,
+   :description: How to use ROCm Compute Profiler's profile mode
+   :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD,
              profiling, profile mode

 ************
 Profile mode
 ************

-The following chapter walks you through Omniperf's core profiling features by
+The following chapter walks you through ROCm Compute Profiler's core profiling features by
 example.

-Learn about analysis with Omniperf in :doc:`../analyze/mode`. For an overview of
-Omniperf's other modes, see :ref:`modes`.
+Learn about analysis with ROCm Compute Profiler in :doc:`../analyze/mode`. For an overview of
+ROCm Compute Profiler's other modes, see :ref:`modes`.

 Profiling
 =========

-Use the ``omniperf`` executable to acquire all necessary performance monitoring
+Use the ``rocprof-compute`` executable to acquire all necessary performance monitoring
 data through analysis of compute workloads.

-Profiling with Omniperf yields the following benefits.
+Profiling with ROCm Compute Profiler yields the following benefits.

-* :ref:`Automate counter collection <profiling-routine>`: Omniperf handles all
+* :ref:`Automate counter collection <profiling-routine>`: ROCm Compute Profiler handles all
  of your profiling via pre-configured input files.

 * :ref:`Filtering <filtering>`: Apply runtime filters to speed up the profiling
@@ -30,7 +30,7 @@ Profiling with Omniperf yields the following benefits.
 * :ref:`Standalone roofline <standalone-roofline>`: Isolate a subset of built-in
  metrics or build your own profiling configuration.

-Run ``omniperf profile -h`` for more details. See
+Run ``rocprof-compute profile -h`` for more details. See
 :ref:`Basic usage <modes-profile>`.

 .. _profile-example:
@@ -38,14 +38,14 @@ Run ``omniperf profile -h`` for more details. See
 Profiling example
 -----------------

-The `<https://github.com/ROCm/omniperf/blob/amd-mainline/sample/vcopy.cpp>`__ repository
+The `<https://github.com/ROCm/rocprofiler-compute/blob/amd-mainline/sample/vcopy.cpp>`__ repository
 includes source code for a sample GPU compute workload, ``vcopy.cpp``. A copy of
 this file is available in the ``share/sample`` subdirectory after a normal
-Omniperf installation, or via the ``$OMNIPERF_SHARE/sample`` directory when
+ROCm Compute Profiler installation, or via the ``$ROCPROFCOMPUTE_SHARE/sample`` directory when
 using the supplied modulefile.

 The examples in this section use a compiled version of the ``vcopy`` workload to
-demonstrate the use of Omniperf in MI accelerator performance analysis. Unless
+demonstrate the use of ROCm Compute Profiler in MI accelerator performance analysis. Unless
 otherwise noted, the performance analysis is done on the
 :ref:`MI200 platform <def-soc>`.

@@ -54,7 +54,7 @@ Workload compilation

 The following example demonstrates compilation of ``vcopy``.

-.. code-block:: shell
+.. code-block:: shell-session

   $ hipcc vcopy.cpp -o vcopy
   $ ls
@@ -74,20 +74,20 @@ The following example demonstrates compilation of ``vcopy``.

 The following sample command profiles the ``vcopy`` workload.

-.. code-block:: shell
+.. code-block:: shell-session

-   $ omniperf profile --name vcopy -- ./vcopy -n 1048576 -b 256
+   $ rocprof-compute profile --name vcopy -- ./vcopy -n 1048576 -b 256

-     ___                  _                  __ 
-    / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-   | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
-   | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-    \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                           |_|                  
+                                    __                                       _
+    _ __ ___   ___ _ __  _ __ ___  / _|       ___ ___  _ __ ___  _ __  _   _| |_ ___
+   | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \
+   | | | (_) | (__| |_) | | | (_) |  _|_____| (_| (_) | | | | | | |_) | |_| | ||  __/
+   |_|  \___/ \___| .__/|_|  \___/|_|        \___\___/|_| |_| |_| .__/ \__,_|\__\___|
+                  |_|                                           |_|

-   Omniperf version: 2.0.0
+   rocprofiler-compute version: 2.0.0
   Profiler choice: rocprofv1
-   Path: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
+   Path: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200
   Target: MI200
   Command: ./vcopy -n 1048576 -b 256
   Kernel Selection: None
@@ -98,10 +98,10 @@ The following sample command profiles the ``vcopy`` workload.
   Collecting Performance Counters
   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

-   [profiling] Current input file: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200/perfmon/SQ_IFETCH_LEVEL.txt
-      |-> [rocprof] RPL: on '240312_174329' from '/opt/rocm-5.2.1' in '/home/auser/repos/omniperf/src/omniperf'
+   [profiling] Current input file: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/perfmon/SQ_IFETCH_LEVEL.txt
+      |-> [rocprof] RPL: on '240312_174329' from '/opt/rocm-5.2.1' in '/home/auser/repos/rocprofiler-compute/src/rocprof-compute'
      |-> [rocprof] RPL: profiling '""./vcopy -n 1048576 -b 256""'
-      |-> [rocprof] RPL: input file '/home/auser/repos/omniperf/sample/workloads/vcopy/MI200/perfmon/SQ_IFETCH_LEVEL.txt'
+      |-> [rocprof] RPL: input file '/home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/perfmon/SQ_IFETCH_LEVEL.txt'
      |-> [rocprof] RPL: output dir '/tmp/rpl_data_240312_174329_692890'
      |-> [rocprof] RPL: result dir '/tmp/rpl_data_240312_174329_692890/input0_results_240312_174329'
      |-> [rocprof] ROCProfiler: input from "/tmp/rpl_data_240312_174329_692890/input0.xml"
@@ -121,15 +121,15 @@ The following sample command profiles the ``vcopy`` workload.
      |-> [rocprof] Finished copying the output vector from the GPU to the CPU
      |-> [rocprof] Releasing GPU memory
      |-> [rocprof] Releasing CPU memory
-      |-> [rocprof] 
+      |-> [rocprof]
     |-> [rocprof] ROCPRofiler: 1 contexts collected, output directory /tmp/rpl_data_240312_174329_692890/input0_results_240312_174329
-       |-> [rocprof] File '/home/auser/repos/omniperf/sample/workloads/vcopy/MI200/SQ_IFETCH_LEVEL.csv' is generating
-      |-> [rocprof] 
-   [profiling] Current input file: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200/perfmon/SQ_INST_LEVEL_LDS.txt
+       |-> [rocprof] File '/home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/SQ_IFETCH_LEVEL.csv' is generating
+      |-> [rocprof]
+   [profiling] Current input file: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/perfmon/SQ_INST_LEVEL_LDS.txt

   ...

-   [roofline] Checking for roofline.csv in /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
+   [roofline] Checking for roofline.csv in /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200
   [roofline] No roofline data found. Generating...
   Empirical Roofline Calculation
   Copyright © 2022  Advanced Micro Devices, Inc. All rights reserved.
@@ -171,9 +171,9 @@ The following sample command profiles the ``vcopy`` workload.

 .. _profiling-routine:

-Notice the two main stages in Omniperf's *default* profiling routine.
+Notice the two main stages in ROCm Compute Profiler's *default* profiling routine.

-1. The first stage collects all the counters needed for Omniperf analysis
+1. The first stage collects all the counters needed for ROCm Compute Profiler analysis
   (omitting any filters you have provided).

 2. The second stage collects data for the roofline analysis (this stage can be
@@ -187,18 +187,18 @@ example:
 * "MI200" for the AMD Instinct MI200 family of accelerators
 * "MI100" for the AMD Instinct MI100 family of accelerators

-The SoC names are generated as a part of Omniperf, and do not *always*
+The SoC names are generated as a part of ROCm Compute Profiler, and do not *always*
 distinguish between different accelerators in the same family; for instance,
 an Instinct MI210 vs an Instinct MI250.

 .. note::

-   Additionally, you will notice a few extra files. An SoC parameters file, 
+   Additionally, you will notice a few extra files. An SoC parameters file,
   ``sysinfo.csv``, is created to reflect the target device settings. All
   profiling output is stored in ``log.txt``. Roofline-specific benchmark
   results are stored in ``roofline.csv``.

-.. code-block:: shell
+.. code-block:: shell-session

   $ ls workloads/vcopy/MI200/
   total 112
@@ -222,8 +222,8 @@ Filtering

 To reduce profiling time and the counters collected, you should use profiling
 filters. Profiling filters and their functionality depend on the underlying
-profiler being used. While Omniperf is profiler-agnostic, this following is a
-detailed description of profiling filters available when using Omniperf with
+profiler being used. While ROCm Compute Profiler is profiler-agnostic, this following is a
+detailed description of profiling filters available when using ROCm Compute Profiler with
 :doc:`ROCProfiler <rocprofiler:index>`.

 Filtering options
@@ -255,7 +255,7 @@ Hardware component filtering
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^

 You can profile specific hardware components to speed up the profiling process.
-In Omniperf, the term hardware block to refers to a hardware component or a
+In ROCm Compute Profiler, the term hardware block to refers to a hardware component or a
 group of hardware components. All profiling results are accumulated in the same
 target directory without overwriting those for other hardware components. This
 enables incremental profiling and analysis.
@@ -263,16 +263,16 @@ enables incremental profiling and analysis.
 The following example only gathers hardware counters for the shader sequencer
 (SQ) and L2 cache (TCC) components, skipping all other hardware components.

-.. code-block:: shell
+.. code-block:: shell-session

-   $ omniperf profile --name vcopy -b SQ TCC -- ./vcopy -n 1048576 -b 256
+   $ rocprof-compute profile --name vcopy -b SQ TCC -- ./vcopy -n 1048576 -b 256

-     ___                  _                  __ 
-    / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-   | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
-   | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-    \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                           |_|                  
+                                    __                                       _
+    _ __ ___   ___ _ __  _ __ ___  / _|       ___ ___  _ __ ___  _ __  _   _| |_ ___
+   | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \
+   | | | (_) | (__| |_) | | | (_) |  _|_____| (_| (_) | | | | | | |_) | |_| | ||  __/
+   |_|  \___/ \___| .__/|_|  \___/|_|        \___\___/|_| |_| |_| .__/ \__,_|\__\___|
+                  |_|                                           |_|

   fname: pmc_cpc_perf: Skipped
   fname: pmc_spi_perf: Skipped
@@ -289,9 +289,9 @@ The following example only gathers hardware counters for the shader sequencer
   fname: pmc_sqc_perf1: Skipped
   fname: pmc_sq_perf6: Added
   fname: pmc_sq_perf2: Added
-   Omniperf version: 2.0.0
+   rocprofiler-compute version: 2.0.0
   Profiler choice: rocprofv1
-   Path: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
+   Path: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200
   Target: MI200
   Command: ./vcopy -n 1048576 -b 256
   Kernel Selection: None
@@ -314,20 +314,20 @@ kernel name substring list to isolate desired kernels.
 The following example demonstrates profiling isolating the kernel matching
 substring ``vecCopy``.

-.. code-block:: shell
+.. code-block:: shell-session

-   $ omniperf profile --name vcopy -k vecCopy -- ./vcopy -n 1048576 -b 256
+   $ rocprof-compute profile --name vcopy -k vecCopy -- ./vcopy -n 1048576 -b 256

-     ___                  _                  __ 
-    / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-   | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
-   | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-    \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                           |_|                  
+                                    __                                       _
+    _ __ ___   ___ _ __  _ __ ___  / _|       ___ ___  _ __ ___  _ __  _   _| |_ ___
+   | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \
+   | | | (_) | (__| |_) | | | (_) |  _|_____| (_| (_) | | | | | | |_) | |_| | ||  __/
+   |_|  \___/ \___| .__/|_|  \___/|_|        \___\___/|_| |_| |_| .__/ \__,_|\__\___|
+                  |_|                                           |_|

-   Omniperf version: 2.0.0
+   rocprofiler-compute version: 2.0.0
   Profiler choice: rocprofv1
-   Path: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
+   Path: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200
   Target: MI200
   Command: ./vcopy -n 1048576 -b 256
   Kernel Selection: ['vecCopy']
@@ -344,25 +344,25 @@ substring ``vecCopy``.
 Dispatch filtering
 ^^^^^^^^^^^^^^^^^^

-Dispatch filtering is based on the *global* dispatch index of kernels in a run. 
+Dispatch filtering is based on the *global* dispatch index of kernels in a run.

 The following example profiles only the first kernel dispatch in the execution
 of the application (note zero-based indexing).

-.. code-block:: shell
+.. code-block:: shell-session

-   $ omniperf profile --name vcopy -d 0 -- ./vcopy -n 1048576 -b 256
+   $ rocprof-compute profile --name vcopy -d 0 -- ./vcopy -n 1048576 -b 256

-     ___                  _                  __ 
-    / _ \ _ __ ___  _ __ (_)_ __   ___ _ __ / _|
-   | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ 
-   | |_| | | | | | | | | | | |_) |  __/ |  |  _|
-    \___/|_| |_| |_|_| |_|_| .__/ \___|_|  |_|  
-                           |_|                  
+                                    __                                       _
+    _ __ ___   ___ _ __  _ __ ___  / _|       ___ ___  _ __ ___  _ __  _   _| |_ ___
+   | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \
+   | | | (_) | (__| |_) | | | (_) |  _|_____| (_| (_) | | | | | | |_) | |_| | ||  __/
+   |_|  \___/ \___| .__/|_|  \___/|_|        \___\___/|_| |_| |_| .__/ \__,_|\__\___|
+                  |_|                                           |_|

-   Omniperf version: 2.0.0
+   rocprofiler-compute version: 2.0.0
   Profiler choice: rocprofv1
-   Path: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
+   Path: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200
   Target: MI200
   Command: ./vcopy -n 1048576 -b 256
   Kernel Selection: None
@@ -381,7 +381,7 @@ Standalone roofline

 If you are only interested in generating roofline analysis data try using
 ``--roof-only``. This will only collect counters relevant to roofline, as well
-as generate a standalone ``.pdf`` output of your roofline plot. 
+as generate a standalone ``.pdf`` output of your roofline plot.

 Roofline options
 ----------------
@@ -408,14 +408,14 @@ Roofline only

 The following example demonstrates profiling roofline data only:

-.. code-block:: shell
+.. code-block:: shell-session

-   $ omniperf profile --name vcopy --roof-only -- ./vcopy -n 1048576 -b 256
+   $ rocprof-compute profile --name vcopy --roof-only -- ./vcopy -n 1048576 -b 256

   ...
-   [roofline] Checking for roofline.csv in /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
+   [roofline] Checking for roofline.csv in /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200
   [roofline] No roofline data found. Generating...
-   Checking for roofline.csv in /home/auser/repos/omniperf/sample/workloads/vcopy/MI200
+   Checking for roofline.csv in /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200
   Empirical Roofline Calculation
   Copyright © 2022  Advanced Micro Devices, Inc. All rights reserved.
   Total detected GPU devices: 4
@@ -427,7 +427,7 @@ The following example demonstrates profiling roofline data only:
 An inspection of our workload output folder shows ``.pdf`` plots were generated
 successfully.

-.. code-block:: shell
+.. code-block:: shell-session

   $ ls workloads/vcopy/MI200/
   total 48
@@ -441,15 +441,14 @@ successfully.

 .. note::

-   Omniperf generates two roofline outputs to organize results and reduce
+   ROCm Compute Profiler generates two roofline outputs to organize results and reduce
   clutter. One chart plots FP32/FP64 performance while the other plots I8/FP16
   performance.

-The following image is a sample ``empirRoof_gpu-ALL_fp32_fp64.pdf`` roofline
+The following image is a sample ``empirRoof_gpu-0_int8_fp16.pdf`` roofline
 plot.

-.. image:: ../../data/profile/sample-roof-plot.png
+.. image:: ../../data/profile/sample-roof-plot.jpg
   :align: center
-   :alt: Sample Omniperf roofline output
+   :alt: Sample ROCm Compute Profiler roofline output
   :width: 800
-
@@ -1,13 +1,13 @@
 .. meta::
-   :description: Omniperf basic usage
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD,
+   :description: ROCm Compute Profiler basic usage
+   :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD,
              basics, usage, operations

 ***********
 Basic usage
 ***********

-The following section outlines basic Omniperf workflows, modes, options, and
+The following section outlines basic ROCm Compute Profiler workflows, modes, options, and
 operations.

 Command line profiler
@@ -18,7 +18,7 @@ Launch and profile the target application using the command line profiler.
 The command line profiler launches the target application, calls the
 ROCProfiler API via the ``rocprof`` binary, and collects profile results for
 the specified kernels, dispatches, and hardware components. If not
-specified, Omniperf defaults to collecting all available counters for all
+specified, ROCm Compute Profiler defaults to collecting all available counters for all
 kernels and dispatches launched by the your executable.

 To collect the default set of data for all kernels in the target
@@ -26,7 +26,7 @@ application, launch, for example:

 .. code-block:: shell

-   $ omniperf profile -n vcopy_data -- ./vcopy -n 1048576 -b 256
+   $ rocprof-compute profile -n vcopy_data -- ./vcopy -n 1048576 -b 256

 This runs the app, launches each kernel, and generates profiling results. By
 default, results are written to a subdirectory with your accelerator's name;
@@ -35,7 +35,7 @@ via the ``-n`` argument.

 .. note::

-   To collect all requested profile information, Omniperf might replay kernels
+   To collect all requested profile information, ROCm Compute Profiler might replay kernels
   multiple times.

 .. _basic-filter-data-collection:
@@ -67,7 +67,7 @@ argument:

 .. code-block:: shell

-   $ omniperf analyze --list-metrics <sys_arch>
+   $ rocprof-compute analyze --list-metrics <sys_arch>

 .. _basic-analyze-cli:

@@ -87,7 +87,7 @@ To interact with profiling results from a different session, provide the
 workload path.

 ``-p``, ``--path``
-   Enables you to analyze existing profiling data in the Omniperf CLI.
+   Enables you to analyze existing profiling data in the ROCm Compute Profiler CLI.

 See :doc:`analyze/cli` for more detailed information.

@@ -97,16 +97,16 @@ Analyze in the Grafana GUI
 --------------------------

 To conduct a more in-depth analysis of profiling results, it's suggested to use
-a Grafana GUI with Omniperf. To interact with profiling results, import your
-data to the MongoDB instance included in the Omniperf Dockerfile. See
+a Grafana GUI with ROCm Compute Profiler. To interact with profiling results, import your
+data to the MongoDB instance included in the ROCm Compute Profiler Dockerfile. See
 :doc:`/install/grafana-setup`.

-To interact with Grafana data, stored in the Omniperf database, enter
+To interact with Grafana data, stored in the ROCm Compute Profiler database, enter
 ``database`` :ref:`mode <modes-database>`; for example:

 .. code-block:: shell

-   $ omniperf database --import [CONNECTION OPTIONS]
+   $ rocprof-compute database --import [CONNECTION OPTIONS]

 See :doc:`/how-to/analyze/grafana-gui` for more detailed information.

@@ -115,7 +115,7 @@ See :doc:`/how-to/analyze/grafana-gui` for more detailed information.
 Modes
 =====

-Modes change the fundamental behavior of the Omniperf command line tool.
+Modes change the fundamental behavior of the ROCm Compute Profiler command line tool.
 Depending on which mode you choose, different command line options become
 available.

@@ -133,10 +133,10 @@ Profile mode

   .. code-block:: shell

-      $ omniperf profile --help
+      $ rocprof-compute profile --help

 See :doc:`profile/mode` to learn about this mode in depth and to get started
-profiling with Omniperf.
+profiling with ROCm Compute Profiler.

 .. _modes-analyze:

@@ -144,24 +144,24 @@ Analyze mode
 ------------

 ``analyze``
-   Loads profiling data from the ``--path`` (``-p``) directory into the Omniperf
+   Loads profiling data from the ``--path`` (``-p``) directory into the ROCm Compute Profiler
   CLI analyzer where you have immediate access to profiling results and
   generated metrics. It generates metrics from the entirety of your profiled
-   application or a subset identified through the Omniperf CLI analysis filters.
+   application or a subset identified through the ROCm Compute Profiler CLI analysis filters.

   To generate a lightweight GUI interface, you can add the ``--gui`` flag to your
   analysis command.

-   This mode is a middle ground to the highly detailed Omniperf Grafana GUI and
+   This mode is a middle ground to the highly detailed ROCm Compute Profiler Grafana GUI and
   is great if you want immediate access to a hardware component you’re already
   familiar with.

   .. code-block:: shell

-      $ omniperf analyze --help
+      $ rocprof-compute analyze --help

 See :doc:`analyze/mode` to learn about this mode in depth and to get started
-with analysis using Omniperf.
+with analysis using ROCm Compute Profiler.

 .. _modes-database:

@@ -178,7 +178,7 @@ Database mode

   .. code-block:: shell

-      $ omniperf database --help
+      $ rocprof-compute database --help

 See :doc:`/install/grafana-setup` to learn about setting up a Grafana server and
 database instance to make your profiling data more digestible and shareable.
@@ -188,11 +188,11 @@ database instance to make your profiling data more digestible and shareable.
 Global options
 ==============

-The Omniperf command line tool has a set of *global* utility options that are
-available across all modes. 
+The ROCm Compute Profiler command line tool has a set of *global* utility options that are
+available across all modes.

 ``-v``, ``--version``
-   Prints the Omniperf version and exits.
+   Prints the ROCm Compute Profiler version and exits.

 ``-V``, ``--verbose``
   Increases output verbosity. Use multiple times for higher levels of
@@ -206,7 +206,7 @@ available across all modes.

 .. note::

-   Omniperf also recognizes the project variable, ``OMNIPERF_COLOR`` should you
+   ROCm Compute Profiler also recognizes the project variable, ``ROCPROFCOMPUTE_COLOR`` should you
   choose to disable colorful output. To disable default colorful behavior, set
   this variable to ``0``.

@@ -215,7 +215,7 @@ available across all modes.
 Basic operations
 ================

-The following table lists Omniperf's basic operations, their
+The following table lists ROCm Compute Profiler's basic operations, their
 :ref:`modes <modes>`, and required arguments.

 .. list-table::
@@ -248,4 +248,3 @@ The following table lists Omniperf's basic operations, their
   * - :doc:`Interact with profiling results from CLI </how-to/analyze/cli>`
     - ``analyze``
     - ``--path``
-
@@ -1,34 +1,34 @@
 .. meta::
-   :description: Omniperf documentation and reference
+   :description: ROCm Compute Profiler documentation and reference
   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD

-**********************
-Omniperf documentation
-**********************
+***********************************
+ROCm Compute Profiler documentation
+***********************************

-Omniperf documentation provides a comprehensive overview of Omniperf.
-In addition to a full deployment guide with installation instructions, this
-documentation also explains the ideas motivating the design behind the tool and
-its components.
+This documentation provides a comprehensive overview of the ROCm Compute
+Profiler tool. In addition to a full deployment guide with installation
+instructions, this documentation also explains the ideas motivating the design
+behind the tool and its components.

-If you're new to Omniperf, familiarize yourself with the tool by reviewing the
+If you're new to ROCm Compute Profiler, familiarize yourself with the tool by reviewing the
 chapters that follow and gradually learn its more advanced features. To get
-started, see :doc:`What is Omniperf? <what-is-omniperf>`.
+started, see :doc:`What is ROCm Compute Profiler? <what-is-rocprof-compute>`.

-Omniperf is open source and hosted at `<https://github.com/ROCm/omniperf>`__.
+ROCm Compute Profiler is open source and hosted at `<https://github.com/ROCm/rocprofiler-compute>`__.

 .. grid:: 2
   :gutter: 3

   .. grid-item-card:: Install

-      * :doc:`install/core-install`
-      * :doc:`Grafana server for Omniperf <install/grafana-setup>`
+      * :doc:`Installation and deployment <install/core-install>`
+      * :doc:`Grafana server for ROCm Compute Profiler <install/grafana-setup>`

   .. grid-item::

-Use the following topics to learn more about the advantages of Omniperf in your
-development toolkit, how it aims to model performance, and how to use Omniperf
+Use the following topics to learn more about the advantages of ROCm Compute Profiler in your
+development toolkit, how it aims to model performance, and how to use ROCm Compute Profiler
 in practice.

 .. grid:: 2
@@ -84,4 +84,3 @@ refer to

 Find ROCm licensing information on the
 `Licensing <https://rocm.docs.amd.com/en/latest/about/license.html>`_ page.
-
@@ -1,15 +1,15 @@
 .. meta::
-   :description: Omniperf installation and deployment
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD,
+   :description: ROCm Compute Profiler installation and deployment
+   :keywords: Omniperf, ROCm Compute Profiler, ROCm, tool, Instinct, accelerator, AMD,
              install, deploy, Grafana, client, configuration, modulefiles

-*********************************
-Installing and deploying Omniperf
-*********************************
+**********************************************
+Installing and deploying ROCm Compute Profiler
+**********************************************

-Omniperf consists of two installation components.
+ROCm Compute Profiler consists of two installation components.

-* :ref:`Omniperf core installation <core-install>` (client-side)
+* :ref:`ROCm Compute Profiler core installation <core-install>` (client-side)

  * Provides the core application profiling capability.
  * Allows the collection of performance counters, filtering by hardware
@@ -17,18 +17,18 @@ Omniperf consists of two installation components.
  * Provides a CLI-based analysis mode.
  * Provides a standalone web interface for importing analysis metrics.

-* :doc:`Grafana server for Omniperf <grafana-setup>` (server-side) (*optional*)
+* :doc:`Grafana server for ROCm Compute Profiler <grafana-setup>` (server-side) (*optional*)

  * Hosts the MongoDB backend and Grafana instance.
  * Is packaged in a Docker container for easy setup.

 Determine what you need to install based on how you would like to interact with
-Omniperf. See the following decision tree to help determine what installation is
+ROCm Compute Profiler. See the following decision tree to help determine what installation is
 right for you.

 .. image:: ../data/install/install-decision-tree.png
   :align: center
-   :alt: Decision tree for installing and deploying Omniperf
+   :alt: Decision tree for installing and deploying ROCm Compute Profiler
   :width: 800

 .. _core-install:
@@ -36,8 +36,8 @@ right for you.
 Core installation
 =================

-The core Omniperf application requires the following basic software
-dependencies. As of ROCm 6.2, the core Omniperf is included with your ROCm
+The core ROCm Compute Profiler application requires the following basic software
+dependencies. As of ROCm 6.2, the core ROCm Compute Profiler is included with your ROCm
 installation.

 * Python ``>= 3.8``
@@ -46,16 +46,16 @@ installation.

 .. note::

-   Omniperf will use the first version of ``Python3`` found in your system's
-   ``PATH``. If the default version of Python3 is older than 3.8, you may need to
-   update your system's ``PATH`` to point to a newer version of Python3.
+   ROCm Compute Profiler will use the first version of ``python3`` found in your system's
+   ``PATH``. If the default version of Python is older than 3.8, you may need to
+   update your system's ``PATH`` to point to a newer version.

-Omniperf depends on a number of Python packages documented in the top-level
-``requirements.txt`` file. Install these *before* configuring Omniperf.
+ROCm Compute Profiler depends on a number of Python packages documented in the top-level
+``requirements.txt`` file. Install these *before* configuring ROCm Compute Profiler.

 .. tip::

-   If looking to build Omniperf as a developer, consider these additional
+   If looking to build ROCm Compute Profiler as a developer, consider these additional
   requirements.

   .. list-table::
@@ -64,23 +64,23 @@ Omniperf depends on a number of Python packages documented in the top-level
         - Python packages required to build this documentation from source.

       * - ``requirements-test.txt``
-         - Python packages required to run Omniperf's CI suite using PyTest.
+         - Python packages required to run ROCm Compute Profiler's CI suite using PyTest.

-The recommended procedure for Omniperf usage is to install into a shared file
+The recommended procedure for ROCm Compute Profiler usage is to install into a shared file
 system so that multiple users can access the final installation. The
 following steps illustrate how to install the necessary Python dependencies
-using `pip <https://packaging.python.org/en/latest/>`_ and Omniperf into a
+using `pip <https://packaging.python.org/en/latest/>`_ and ROCm Compute Profiler into a
 shared location controlled by the ``INSTALL_DIR`` environment variable.

 .. tip::

-   To always run Omniperf with a particular version of python, you can create a
-   bash alias. For example, to run Omniperf with Python 3.10, you can run the
+   To always run ROCm Compute Profiler with a particular version of Python, you can create a
+   bash alias. For example, to run ROCm Compute Profiler with Python 3.10, you can run the
   following command:

   .. code-block:: shell

-      alias omniperf-mypython="/usr/bin/python3.10 /opt/rocm/bin/omniperf"
+      alias rocprof-compute-mypython="/usr/bin/python3.10 /opt/rocm/bin/rocprof-compute"

 .. _core-install-cmake-vars:

@@ -97,13 +97,13 @@ follows.
      - Description

    * - ``CMAKE_INSTALL_PREFIX``
-      - Controls the install path for Omniperf files.
+      - Controls the install path for ROCm Compute Profiler files.

    * - ``PYTHON_DEPS``
      - Specifies an optional path to resolve Python package dependencies.

    * - ``MOD_INSTALL_PATH``
-      - Specifies an optional path for separate Omniperf modulefile installation.
+      - Specifies an optional path for separate ROCm Compute Profiler modulefile installation.

 .. _core-install-steps:

@@ -111,20 +111,20 @@ Install from source
 -------------------

 #. A typical install begins by downloading the latest release tarball available
-   from `<https://github.com/ROCm/omniperf/releases>`__. From there, untar and
+   from `<https://github.com/ROCm/rocprofiler-compute/releases>`__. From there, untar and
   navigate into the top-level directory.

   ..
-      {{ config.version }} substitutes the Omniperf version in ../conf.py
+      {{ config.version }} substitutes the ROCm Compute Profiler version in ../conf.py

   .. datatemplate:nodata::

      .. code-block:: shell

-         tar xfz omniperf-v{{ config.version }}.tar.gz
-         cd omniperf-v{{ config.version }}
+         tar xfz rocprofiler-compute-v{{ config.version }}.tar.gz
+         cd rocprofiler-compute-v{{ config.version }}

-#. Next, install Python dependencies and complete the Omniperf configuration and
+#. Next, install Python dependencies and complete the ROCm Compute Profiler configuration and
   install process.

   .. datatemplate:nodata::
@@ -137,12 +137,12 @@ Install from source
         # install python deps
         python3 -m pip install -t ${INSTALL_DIR}/python-libs -r requirements.txt

-         # configure Omniperf for shared install
+         # configure ROCm Compute Profiler for shared install
         mkdir build
         cd build
         cmake -DCMAKE_INSTALL_PREFIX=${INSTALL_DIR}/{{ config.version }} \
                 -DPYTHON_DEPS=${INSTALL_DIR}/python-libs \
-                 -DMOD_INSTALL_PATH=${INSTALL_DIR}/modulefiles/omniperf ..
+                 -DMOD_INSTALL_PATH=${INSTALL_DIR}/modulefiles/rocprofiler-compute ..

         # install
         make install
@@ -169,33 +169,33 @@ Execution using modulefiles

 The installation process includes the creation of an environment modulefile for
 use with `Lmod <https://lmod.readthedocs.io>`_. On systems that support Lmod,
-you can register the Omniperf modulefile directory and setup your environment
-for execution of Omniperf as follows.
+you can register the ROCm Compute Profiler modulefile directory and setup your environment
+for execution of ROCm Compute Profiler as follows.

 .. datatemplate:nodata::

   .. code-block:: shell

      $ module use $INSTALL_DIR/modulefiles
-      $ module load omniperf
-      $ which omniperf
-      /opt/apps/omniperf/{{ config.version }}/bin/omniperf
+      $ module load rocprofiler-compute
+      $ which rocprof-compute
+      /opt/apps/rocprofiler-compute/{{ config.version }}/bin/rocprof-compute

-      $ omniperf --version
+      $ rocprof-compute --version
      ROC Profiler:   /opt/rocm-5.1.0/bin/rocprof

-      omniperf (v{{ config.version }})
+      rocprofiler-compute (v{{ config.version }})

 .. tip::

   If you're relying on an Lmod Python module locally, you may wish to customize
-   the resulting Omniperf modulefile post-installation to include extra
+   the resulting ROCm Compute Profiler modulefile post-installation to include extra
   module dependencies.

 Execution without modulefiles
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

-To use Omniperf without the companion modulefile, update your ``PATH``
+To use ROCm Compute Profiler without the companion modulefile, update your ``PATH``
 settings to enable access to the command line binary. If you installed Python
 dependencies in a shared location, also update your ``PYTHONPATH``
 configuration.
@@ -212,7 +212,7 @@ configuration.
 Install via package manager
 ---------------------------

-Once ROCm (minimum version 6.2.0) is installed, you can install Omniperf using
+Once ROCm (minimum version 6.2.0) is installed, you can install ROCm Compute Profiler using
 your operating system's native package manager using the following commands.
 See :doc:`rocm-install-on-linux:index` for guidance on installing the ROCm
 software stack.
@@ -223,39 +223,38 @@ software stack.

      .. code-block:: shell

-         $ sudo apt install omniperf
-         # Include omniperf in your system PATH
-         $ sudo update-alternatives --install /usr/bin/omniperf omniperf /opt/rocm/bin/omniperf 0
+         $ sudo apt install rocprofiler-compute
+         # Include rocprofiler-compute in your system PATH
+         $ sudo update-alternatives --install /usr/bin/rocprofiler-compute rocprof-compute /opt/rocm/bin/rocprofiler-compute 0
         # Install Python dependencies
-         $ python3 -m pip install -r /opt/rocm/libexec/omniperf/requirements.txt
+         $ python3 -m pip install -r /opt/rocm/libexec/rocprofiler-compute/requirements.txt

   .. tab-item:: Red Hat Enterprise Linux

      .. code-block:: shell

-         $ sudo dnf install omniperf
-         # Include omniperf in your system PATH
-         $ sudo update-alternatives --install /usr/bin/omniperf omniperf /opt/rocm/bin/omniperf 0
+         $ sudo dnf install rocprofiler-compute
+         # Include rocprofiler-compute in your system PATH
+         $ sudo update-alternatives --install /usr/bin/rocprofiler-compute rocprof-compute /opt/rocm/bin/rocprofiler-compute 0
         # Install Python dependencies
-         $ python3 -m pip install -r /opt/rocm/libexec/omniperf/requirements.txt
+         $ python3 -m pip install -r /opt/rocm/libexec/rocprofiler-compute/requirements.txt

   .. tab-item:: SUSE Linux Enterprise Server

      .. code-block:: shell

-         $ sudo zypper install omniperf
-         # Include omniperf in your system PATH
-         $ sudo update-alternatives --install /usr/bin/omniperf omniperf /opt/rocm/bin/omniperf 0
+         $ sudo zypper install rocprofiler-compute
+         # Include rocprofiler-compute in your system PATH
+         $ sudo update-alternatives --install /usr/bin/rocprofiler-compute rocprof-compute /opt/rocm/bin/rocprofiler-compute 0
         # Install Python dependencies
-         $ python3 -m pip install -r /opt/rocm/libexec/omniperf/requirements.txt
+         $ python3 -m pip install -r /opt/rocm/libexec/rocprofiler-compute/requirements.txt

 .. _core-install-rocprof-var:

 ROCProfiler
 -----------

-Omniperf relies on :doc:`ROCProfiler <rocprofiler:index>`'s ``rocprof`` binary
+ROCm Compute Profiler relies on :doc:`ROCProfiler <rocprofiler:index>`'s ``rocprof`` binary
 during the profiling process. Normally, the path to this binary is detected
 automatically, but you can override the path by the setting the optional
 ``ROCPROF`` environment variable.
-
@@ -1,26 +1,26 @@
 .. meta::
-   :description: Omniperf Grafana server installation and deployment
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD,
+   :description: ROCm Compute Profiler Grafana server installation and deployment
+   :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD,
              install, deploy, Grafana, server, configuration, GUI

-****************************************
-Setting up a Grafana server for Omniperf
-****************************************
+***************************************************
+Setting up Grafana server for ROCm Compute Profiler
+***************************************************

 A Grafana server is *not required* to profile or analyze performance data
 from the CLI. It's a supplementary mechanism to help you import performance
 data and examine it in a detailed
 `Grafana <https://github.com/grafana/grafana>`_ dashboard GUI.

-Learn about installing and configuring the main Omniperf tool in
+Learn about installing and configuring the main ROCm Compute Profiler tool in
 :ref:`core-install`.

-Setting up a Grafana instance for Omniperf requires the following basic software
+Setting up a Grafana instance for ROCm Compute Profiler requires the following basic software
 dependencies.

 * `Docker Engine <https://docs.docker.com/engine/install/>`_

-The recommended process for enabling the server-side of Omniperf is to use the
+The recommended process for enabling the server-side of ROCm Compute Profiler is to use the
 provided ``Dockerfile`` to build the Grafana and MongoDB instance.

 .. _grafana-mongodb-setup:
@@ -34,7 +34,7 @@ the following setup instructions.
 Install MongoDB utilities
 -------------------------

-Omniperf uses the
+ROCm Compute Profiler uses the
 `mongoimport <https://www.mongodb.com/docs/database-tools/mongoimport/>`_
 utility to upload data to your Grafana instance's backend database.

@@ -70,7 +70,7 @@ crash or reset. This is called *creating a persistent volume*.
 Build and launch the Docker container
 -------------------------------------

-You're now ready to build your ``Dockerfile``. Navigate to your Omniperf install
+You're now ready to build your ``Dockerfile``. Navigate to your ROCm Compute Profiler install
 directory to begin.

 .. code-block:: bash
@@ -79,6 +79,13 @@ directory to begin.
   $ sudo docker-compose build
   $ sudo docker-compose up -d

+.. note::
+
+   To troubleshoot Docker container build failures related to certificate verification, try
+   disabling any network proxy services on the host system. These proxy services can interfere
+   with OpenSSL's ability to retrieve a correct certificate chain when the container accesses
+   external websites.
+
 The TCP ports for Grafana (``4000``) and MongoDB (``27017``) in the Docker
 container are mapped to ``14000`` and ``27018``, respectively, on the host side.

@@ -158,12 +165,12 @@ connection is successful.

 .. _grafana-import-dashboard-file:

-Import the Omniperf dashboard file
----------------------------------
+Import the ROCm Compute Profiler dashboard file
+-----------------------------------------------

 From the **Create** → **Import** page, upload the dashboard file,
 ``/dashboards/Omniperf_v{__VERSION__}_pub.json`` from the
-:doc:`Omniperf tarball <core-install>`.
+:doc:`ROCm Compute Profiler tarball <core-install>`.

 Edit both the dashboard **Name** and the **Unique identifier (UID)** fields to
 uniquely identify the dashboard. Click **Import** to complete the process.
@@ -177,21 +184,21 @@ uniquely identify the dashboard. Click **Import** to complete the process.

 .. _grafana-select-workload:

-Select and load the Omniperf workload
-------------------------------------
+Select and load the ROCm Compute Profiler workload
+--------------------------------------------------

 Once you have imported a dashboard you're ready to begin. Start by browsing
 available dashboards and selecting the dashboard you have just imported.

 .. figure:: ../data/install/opening_dashboard.png
   :align: center
-   :alt: Opening your Omniperf dashboard in Grafana
+   :alt: Opening your ROCm Compute Profiler dashboard in Grafana
   :width: 800

-   Opening your Omniperf profiling dashboard in Grafana.
+   Opening your ROCm Compute Profiler profiling dashboard in Grafana.

 Remember that you need to upload workload data to the MongoDB backend before
-analyzing in your Grafana interface. See a detailed example of this in 
+analyzing in your Grafana interface. See a detailed example of this in
 :ref:`grafana-gui-import`.

 After a workload has been successfully uploaded, you should be able to select it
@@ -199,11 +206,10 @@ from the workload dropdown located at the top of your Grafana dashboard.

 .. figure:: ../data/install/grafana_workload_selection.png
   :align: center
-   :alt: Omniperf workload selection in Grafana
+   :alt: ROCm Compute Profiler workload selection in Grafana
   :width: 800

-   Selecting your Omniperf workload in Grafana.
+   Selecting your ROCm Compute Profiler workload in Grafana.

 For more information on how to use the Grafana interface for analysis see
 :doc:`/how-to/analyze/grafana-gui`.
-
@@ -1,6 +1,6 @@
 .. meta::
-   :description: Omniperf license
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD,
+   :description: ROCm Compute Profiler license
+   :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD,
              license

 *******
@@ -1,36 +1,36 @@
 .. meta::
-   :description: Omniperf support: compatible accelerators and GPUs
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, GPU
+   :description: ROCm Compute Profiler support: compatible accelerators and GPUs
+   :keywords: Omniperf, compatible, cdna, gcn, gfx, rdna, radeon, hardware, architecture

 ***********************
 Compatible accelerators
 ***********************

 The following table lists SoCs (System on Chip) tested for compatibility with
-Omniperf. See :doc:`rocm:reference/gpu-arch-specs` for full AMD accelerator and
+ROCm Compute Profiler. See :doc:`rocm:reference/gpu-arch-specs` for full AMD accelerator and
 GPU specifications.

 .. _def-soc:

 .. note::

-   In Omniperf documentation, the term System on Chip (SoC) refers to a
+   In ROCm Compute Profiler documentation, the term System on Chip (SoC) refers to a
   particular family of AMD accelerators.

 .. list-table::
-    :header-rows: 1
+   :header-rows: 1

-    * - Platform
-      - Status
+   * - Platform
+     - Status

-    * - AMD Instinct™ MI300
-      - Supported ✅
+   * - AMD Instinct™ MI300
+     - Supported ✅

-    * - AMD Instinct MI200
-      - Supported ✅
+   * - AMD Instinct MI200
+     - Supported ✅

-    * - AMD Instinct MI100
-      - Supported ✅
+   * - AMD Instinct MI100
+     - Supported ✅

-    * - AMD Instinct MI50, MI60 (Vega 20)
-      - No support ❌
+   * - AMD Instinct MI50, MI60 (Vega 20)
+     - No support ❌
@@ -1,6 +1,6 @@
 .. meta::
-    :description: Omniperf FAQ and troubleshooting
-    :keywords: Omniperf, FAQ, troubleshooting, ROCm, profiler, tool, Instinct,
+    :description: ROCm Compute Profiler FAQ and troubleshooting
+    :keywords: ROCm Compute Profiler, FAQ, troubleshooting, ROCm, profiler, tool, Instinct,
               accelerator, AMD, SSH, error, version, workaround, help

 ***
@@ -9,8 +9,8 @@ FAQ

 Frequently asked questions and troubleshooting tips.

-How do I export profiling data I have already generated using Omniperf?
-=======================================================================
+How do I export profiling data I have already generated using ROCm Compute Profiler?
+====================================================================================

 To interact with the Grafana GUI, you must sync data with the MongoDB
 backend. You can do this using :ref:`database <modes-database>` mode.
@@ -19,7 +19,7 @@ Pass in the directory of your desired workload as follows.

 .. code-block:: shell

-    $ omniperf database --import -w <path-to-results> -H <hostname> -u <username> -t <team-name>
+    $ rocprof-compute database --import -w <path-to-results> -H <hostname> -u <username> -t <team-name>

 python ast error: 'Constant' object has no attribute 'kind'
 ===========================================================
@@ -6,13 +6,14 @@ defaults:
 root: index
 subtrees:
  - entries:
-    - file: what-is-omniperf.rst
+    - file: what-is-rocprof-compute.rst

  - caption: Install
    entries:
    - file: install/core-install.rst
+      title: Installation and deployment
    - file: install/grafana-setup.rst
-      title: Grafana server for Omniperf
+      title: Grafana server setup

  - caption: How to
    entries:
@@ -1,2 +1,2 @@
-rocm-docs-core==1.6.1
+rocm-docs-core==1.12.0
 sphinxcontrib.datatemplates==0.11.0
@@ -6,9 +6,9 @@
 #
 accessible-pygments==0.0.5
    # via pydata-sphinx-theme
-alabaster==0.7.16
+alabaster==1.0.0
    # via sphinx
-babel==2.15.0
+babel==2.16.0
    # via
    #   pydata-sphinx-theme
    #   sphinx
@@ -16,21 +16,21 @@ beautifulsoup4==4.12.3
    # via pydata-sphinx-theme
 breathe==4.35.0
    # via rocm-docs-core
-certifi==2024.7.4
+certifi==2024.8.30
    # via requests
-cffi==1.16.0
+cffi==1.17.1
    # via
    #   cryptography
    #   pynacl
-charset-normalizer==3.3.2
+charset-normalizer==3.4.0
    # via requests
 click==8.1.7
    # via sphinx-external-toc
-cryptography==43.0.0
+cryptography==43.0.3
    # via pyjwt
 defusedxml==0.7.1
    # via sphinxcontrib-datatemplates
-deprecated==1.2.14
+deprecated==1.2.15
    # via pygithub
 docutils==0.21.2
    # via
@@ -44,7 +44,7 @@ gitdb==4.0.11
    # via gitpython
 gitpython==3.1.43
    # via rocm-docs-core
-idna==3.7
+idna==3.10
    # via requests
 imagesize==1.4.1
    # via sphinx
@@ -56,36 +56,34 @@ markdown-it-py==3.0.0
    # via
    #   mdit-py-plugins
    #   myst-parser
-markupsafe==2.1.5
+markupsafe==3.0.2
    # via jinja2
-mdit-py-plugins==0.4.1
+mdit-py-plugins==0.4.2
    # via myst-parser
 mdurl==0.1.2
    # via markdown-it-py
-myst-parser==3.0.1
+myst-parser==4.0.0
    # via rocm-docs-core
-packaging==24.1
-    # via
-    #   pydata-sphinx-theme
-    #   sphinx
+packaging==24.2
+    # via sphinx
 pycparser==2.22
    # via cffi
-pydata-sphinx-theme==0.15.4
+pydata-sphinx-theme==0.16.0
    # via
    #   rocm-docs-core
    #   sphinx-book-theme
-pygithub==2.3.0
+pygithub==2.5.0
    # via rocm-docs-core
 pygments==2.18.0
    # via
    #   accessible-pygments
    #   pydata-sphinx-theme
    #   sphinx
-pyjwt[crypto]==2.8.0
+pyjwt[crypto]==2.10.0
    # via pygithub
 pynacl==1.5.0
    # via pygithub
-pyyaml==6.0.1
+pyyaml==6.0.2
    # via
    #   myst-parser
    #   rocm-docs-core
@@ -95,15 +93,15 @@ requests==2.32.3
    # via
    #   pygithub
    #   sphinx
-rocm-docs-core==1.6.1
+rocm-docs-core==1.12.0
    # via -r requirements.in
 smmap==5.0.1
    # via gitdb
 snowballstemmer==2.2.0
    # via sphinx
-soupsieve==2.5
+soupsieve==2.6
    # via beautifulsoup4
-sphinx==7.4.7
+sphinx==8.1.3
    # via
    #   breathe
    #   myst-parser
@@ -120,37 +118,37 @@ sphinx-book-theme==1.1.3
    # via rocm-docs-core
 sphinx-copybutton==0.5.2
    # via rocm-docs-core
-sphinx-design==0.6.0
+sphinx-design==0.6.1
    # via rocm-docs-core
 sphinx-external-toc==1.0.1
    # via rocm-docs-core
-sphinx-notfound-page==1.0.2
+sphinx-notfound-page==1.0.4
    # via rocm-docs-core
-sphinxcontrib-applehelp==1.0.8
+sphinxcontrib-applehelp==2.0.0
    # via sphinx
 sphinxcontrib-datatemplates==0.11.0
    # via -r requirements.in
-sphinxcontrib-devhelp==1.0.6
+sphinxcontrib-devhelp==2.0.0
    # via sphinx
-sphinxcontrib-htmlhelp==2.0.6
+sphinxcontrib-htmlhelp==2.1.0
    # via sphinx
 sphinxcontrib-jsmath==1.0.1
    # via sphinx
-sphinxcontrib-qthelp==1.0.8
+sphinxcontrib-qthelp==2.0.0
    # via sphinx
 sphinxcontrib-runcmd==0.2.0
    # via sphinxcontrib-datatemplates
-sphinxcontrib-serializinghtml==1.1.10
+sphinxcontrib-serializinghtml==2.0.0
    # via sphinx
-tomli==2.0.1
+tomli==2.1.0
    # via sphinx
 typing-extensions==4.12.2
    # via
    #   pydata-sphinx-theme
    #   pygithub
-urllib3==2.2.2
+urllib3==2.2.3
    # via
    #   pygithub
    #   requests
-wrapt==1.16.0
+wrapt==1.17.0
    # via deprecated
@@ -1,30 +1,8 @@
-:root {
-    --amd-teal-500: #00C2DE;
-    --amd-teal-750: #00788E;
-}
-
 /* Override PyData Sphinx Theme default colors */
 html[data-theme='light'] {
-    --pst-color-primary: var(--amd-teal-750);
-    --pst-color-primary-bg: var(--amd-teal-500);
    --pst-color-table-row-hover-bg: #E2E8F0;
 }

 html[data-theme='dark'] {
-    --pst-color-primary: var(--amd-teal-500);
-    --pst-color-primary-bg: var(--amd-teal-750);
    --pst-color-table-row-hover-bg: #1E293B;
 }
-
-html[data-theme='light'],
-html[data-theme='dark'] {
-    --pst-color-link: var(--pst-color-primary);
-}
-
-a svg {
-  color: var(--pst-color-text-base);
-}
-
-a svg:hover {
-  color: var(--pst-color-link-hover);
-}
@@ -5,7 +5,7 @@ Infinity Fabric transactions

 For this example, consider the
 :dev-sample:`Infinity Fabric™ sample <fabric.hip>` distributed as a part of
- Omniperf.
+ ROCm Compute Profiler.

 This following code snippet launches a simple read-only kernel.

@@ -36,7 +36,7 @@ is identically false -- and thus we expect no writes.

 .. note::

-   The actual sample included with Omniperf also includes the ability to select
+   The actual sample included with ROCm Compute Profiler also includes the ability to select
   different operation types (such as atomics, writes). This abbreviated version
   is presented here for reference only.

@@ -44,13 +44,13 @@ Finally, this sample code lets the user control the
 :ref:`granularity of an allocation <memory-type>`, the owner of an allocation
 (local HBM, CPU DRAM or remote HBM), and the size of an allocation (the default
 is :math:`\sim4`\ GiB) via command line arguments. In doing so, we can explore
-the impact of these parameters on the L2-Fabric metrics reported by Omniperf to
+the impact of these parameters on the L2-Fabric metrics reported by ROCm Compute Profiler to
 further understand their meaning.

 .. note::

   All results in this section were generated an a node of Infinity
-   Fabric connected MI250 accelerators using ROCm version 5.6.0, and Omniperf
+   Fabric connected MI250 accelerators using ROCm version 5.6.0, and ROCm Compute Profiler
   version 2.0.0. Although results may vary with ROCm versions and accelerator
   connectivity, we expect the lessons learned here to be broadly applicable.

@@ -64,7 +64,7 @@ In our first experiment, we consider the simplest possible case, a

 .. code-block:: shell-session

-   $ omniperf profile -n coarse_grained_local --no-roof -- ./fabric -t 1 -o 0
+   $ rocprof-compute profile -n coarse_grained_local --no-roof -- ./fabric -t 1 -o 0
   Using:
     mtype:CoarseGrained
     mowner:Device
@@ -73,7 +73,7 @@ In our first experiment, we consider the simplest possible case, a
     mdata:Unsigned
     remoteId:-1
   <...>
-   $ omniperf analyze -p workloads/coarse_grained_local/mi200 -b 17.2.0 17.2.1 17.2.2 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2
+   $ rocprof-compute analyze -p workloads/coarse_grained_local/mi200 -b 17.2.0 17.2.1 17.2.2 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2
   <...>
   17. L2 Cache
   17.2 L2 - Fabric Transactions
@@ -163,7 +163,7 @@ accelerator. Our code uses the ``hipExtMallocWithFlag`` API with the

 .. code-block:: shell-session

-   $ omniperf profile -n fine_grained_local --no-roof -- ./fabric -t 0 -o 0
+   $ rocprof-compute profile -n fine_grained_local --no-roof -- ./fabric -t 0 -o 0
   Using:
     mtype:FineGrained
     mowner:Device
@@ -172,7 +172,7 @@ accelerator. Our code uses the ``hipExtMallocWithFlag`` API with the
     mdata:Unsigned
     remoteId:-1
   <...>
-   $ omniperf analyze -p workloads/fine_grained_local/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4  -n per_kernel --dispatch 2
+   $ rocprof-compute analyze -p workloads/fine_grained_local/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4  -n per_kernel --dispatch 2
   <...>
   17. L2 Cache
   17.2 L2 - Fabric Transactions
@@ -245,7 +245,7 @@ substantial change in the L2-Fabric metrics:

 .. code-block:: shell-session

-   $ omniperf profile -n fine_grained_remote --no-roof -- ./fabric -t 0 -o 2
+   $ rocprof-compute profile -n fine_grained_remote --no-roof -- ./fabric -t 0 -o 2
   Using:
     mtype:FineGrained
     mowner:Remote
@@ -254,7 +254,7 @@ substantial change in the L2-Fabric metrics:
     mdata:Unsigned
     remoteId:-1
   <...>
-   $ omniperf analyze -p workloads/fine_grained_remote/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4  -n per_kernel --dispatch 2
+   $ rocprof-compute analyze -p workloads/fine_grained_remote/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4  -n per_kernel --dispatch 2
   <...>
   17. L2 Cache
   17.2 L2 - Fabric Transactions
@@ -339,7 +339,7 @@ fine-grained memory using the ``hipHostMalloc`` API:

 .. code-block:: shell-session

-   $ omniperf profile -n fine_grained_host --no-roof -- ./fabric -t 0 -o 1
+   $ rocprof-compute profile -n fine_grained_host --no-roof -- ./fabric -t 0 -o 1
   Using:
     mtype:FineGrained
     mowner:Host
@@ -348,7 +348,7 @@ fine-grained memory using the ``hipHostMalloc`` API:
     mdata:Unsigned
     remoteId:-1
   <...>
-   $ omniperf analyze -p workloads/fine_grained_host/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4  -n per_kernel --dispatch 2
+   $ rocprof-compute analyze -p workloads/fine_grained_host/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4  -n per_kernel --dispatch 2
   <...>
   17. L2 Cache
   17.2 L2 - Fabric Transactions
@@ -416,7 +416,7 @@ allocation as coarse-grained:

 .. code-block:: shell-session

-   $ omniperf profile -n coarse_grained_host --no-roof -- ./fabric -t 1 -o 1
+   $ rocprof-compute profile -n coarse_grained_host --no-roof -- ./fabric -t 1 -o 1
   Using:
     mtype:CoarseGrained
     mowner:Host
@@ -425,7 +425,7 @@ allocation as coarse-grained:
     mdata:Unsigned
     remoteId:-1
   <...>
-   $ omniperf analyze -p workloads/coarse_grained_host/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4  -n per_kernel --dispatch 2
+   $ rocprof-compute analyze -p workloads/coarse_grained_host/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4  -n per_kernel --dispatch 2
   <...>
   17. L2 Cache
   17.2 L2 - Fabric Transactions
@@ -484,7 +484,7 @@ operations to fine-grained memory allocated on the host:

 .. code-block:: shell-session

-   $ omniperf profile -n fine_grained_host_write --no-roof -- ./fabric -t 0 -o 1 -p 1
+   $ rocprof-compute profile -n fine_grained_host_write --no-roof -- ./fabric -t 0 -o 1 -p 1
   Using:
     mtype:FineGrained
     mowner:Host
@@ -493,7 +493,7 @@ operations to fine-grained memory allocated on the host:
     mdata:Unsigned
     remoteId:-1
   <...>
-   $ omniperf analyze -p workloads/fine_grained_host_writes/mi200 -b 17.2.4 17.2.5 17.2.6 17.2.7 17.2.8 17.4.3 17.4.4 17.4.5 17.4.6 17.5.5 17.5.6 17.5.7 17.5.8 17.5.9 17.5.10 -n per_kernel --dispatch 2
+   $ rocprof-compute analyze -p workloads/fine_grained_host_writes/mi200 -b 17.2.4 17.2.5 17.2.6 17.2.7 17.2.8 17.4.3 17.4.4 17.4.5 17.4.6 17.5.5 17.5.6 17.5.7 17.5.8 17.5.9 17.5.10 -n per_kernel --dispatch 2
   <...>
   17. L2 Cache
   17.2 L2 - Fabric Transactions
@@ -576,7 +576,7 @@ operations to the CPU’s DRAM.

 .. code-block:: shell-session

-   $ omniperf profile -n fine_grained_host_add --no-roof -- ./fabric -t 0 -o 1 -p 2
+   $ rocprof-compute profile -n fine_grained_host_add --no-roof -- ./fabric -t 0 -o 1 -p 2
   Using:
     mtype:FineGrained
     mowner:Host
@@ -585,7 +585,7 @@ operations to the CPU’s DRAM.
     mdata:Unsigned
     remoteId:-1
   <...>
-   $ omniperf analyze -p workloads/fine_grained_host_add/mi200 -b 17.2.4 17.2.5 17.2.6 17.2.7 17.2.8 17.4.3 17.4.4 17.4.5 17.4.6 17.5.5 17.5.6 17.5.7 17.5.8 17.5.9 17.5.10 -n per_kernel --dispatch 2
+   $ rocprof-compute analyze -p workloads/fine_grained_host_add/mi200 -b 17.2.4 17.2.5 17.2.6 17.2.7 17.2.8 17.4.3 17.4.4 17.4.5 17.4.6 17.5.5 17.5.6 17.5.7 17.5.8 17.5.9 17.5.10 -n per_kernel --dispatch 2
   <...>
   17. L2 Cache
   17.2 L2 - Fabric Transactions
@@ -5,7 +5,7 @@ Instructions-per-cycle and utilizations example

 For this example, consider the
 :dev-sample:`instructions-per-cycle (IPC) example <ipc.hip>` included with
-Omniperf.
+ROCm Compute Profiler.

 This example is compiled using ``c++17`` support:

@@ -17,7 +17,7 @@ and was run on an MI250 CDNA2 accelerator:

 .. code-block:: shell

-   $ omniperf profile -n ipc --no-roof -- ./ipc
+   $ rocprof-compute profile -n ipc --no-roof -- ./ipc

 The results shown in this section are *generally* applicable to CDNA
 accelerators, but may vary between generations and specific products.
@@ -64,11 +64,11 @@ operation, i.e., a ``v_mov_b32`` instruction, e.g.:

 This instruction simply copies the contents from the source register
 (``v1``) to the destination register (``v0``). Investigating this kernel
-with Omniperf, we see:
+with ROCm Compute Profiler, we see:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 7 -b 11.2
+   $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 7 -b 11.2
   <...>
   --------------------------------------------------------------------------------
   0. Top Stat
@@ -172,7 +172,7 @@ in the IPC example:

 .. code-block:: shell

-   $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 8 -b 11.2 --decimal 4
+   $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 8 -b 11.2 --decimal 4
   <...>
   --------------------------------------------------------------------------------
   0. Top Stat
@@ -240,7 +240,7 @@ instructions executed over the total
   There are further complications of the Issued IPC metric (**11.2.1**) that make
   its use more complicated. We will be explore that in the
   :ref:`following section <ipc-internal-instructions>`. For these reasons,
-   Omniperf typically promotes use of the regular IPC metric (**11.2.0**), e.g., in
+   ROCm Compute Profiler typically promotes use of the regular IPC metric (**11.2.0**), e.g., in
   the top-level Speed-of-Light chart.

 .. _ipc-internal-instructions:
@@ -261,11 +261,11 @@ Here we choose to use the following no-op to make our point:

   s_nop 0x0

-Running this kernel through Omniperf yields:
+Running this kernel through ROCm Compute Profiler yields:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 9 -b 11.2
+   $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 9 -b 11.2
   <...>
   --------------------------------------------------------------------------------
   0. Top Stat
@@ -362,11 +362,11 @@ operation, for instance:

 which, in analogue to our :ref:`v_mov <ipc-valu-utilization>` example, copies the
 contents of the source scalar register (``s1``) to the destination
-scalar register (``s0``). Running this kernel through Omniperf yields:
+scalar register (``s0``). Running this kernel through ROCm Compute Profiler yields:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 10 -b 11.2
+   $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 10 -b 11.2
   <...>
   --------------------------------------------------------------------------------
   0. Top Stat
@@ -426,11 +426,11 @@ of our :ref:`v_mov <ipc-valu-utilization>` example:

 That is, we wrap our :ref:`VALU <desc-valu>` operation inside a conditional
 where only one lane in our wavefront is active. Running this kernel
-through Omniperf yields:
+through ROCm Compute Profiler yields:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 11 -b 11.2
+   $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 11 -b 11.2
   <...>
   --------------------------------------------------------------------------------
   0. Top Stat
@@ -4,22 +4,22 @@ LDS examples
 ============

 For this example, consider the
-:dev-sample:`LDS sample <lds.hip>` distributed as a part of Omniperf. This
+:dev-sample:`LDS sample <lds.hip>` distributed as a part of ROCm Compute Profiler. This
 code contains two kernels to explore how both :doc:`LDS </conceptual/local-data-share>` bandwidth and
-bank conflicts are calculated in Omniperf.
+bank conflicts are calculated in ROCm Compute Profiler.

 This example was compiled and run on an MI250 accelerator using ROCm
-v5.6.0, and Omniperf v2.0.0.
+v5.6.0, and ROCm Compute Profiler v2.0.0.

 .. code-block:: shell-session

   $ hipcc -O3 lds.hip -o lds

-Finally, we generate our ``omniperf profile`` as:
+Finally, we generate our ``rocprof-compute profile`` as:

 .. code-block:: shell-session

-   $ omniperf profile -n lds --no-roof -- ./lds
+   $ rocprof-compute profile -n lds --no-roof -- ./lds

 .. _lds-bandwidth:

@@ -71,7 +71,7 @@ Next, let’s analyze the first of our bandwidth kernel dispatches:

 .. code-block:: shell

-   $ omniperf analyze -p workloads/lds/mi200/ -b 12.2.1 --dispatch 0 -n per_kernel
+   $ rocprof-compute analyze -p workloads/lds/mi200/ -b 12.2.1 --dispatch 0 -n per_kernel
   <...>
   12. Local Data Share (LDS)
   12.2 LDS Stats
@@ -93,7 +93,7 @@ Recall our definition of this metric:

 Here we see that this instruction *could* have loaded up to 256 bytes of
 data (4 bytes for each work-item in the wavefront), and therefore this
-is the expected value for this metric in Omniperf, hence why this metric
+is the expected value for this metric in ROCm Compute Profiler, hence why this metric
 is named the “theoretical” bandwidth.

 To further illustrate this point we plot the relationship of the
@@ -104,11 +104,11 @@ launched from 1 to 256:
 .. figure:: ../data/profiling-by-example/ldsbandwidth.png
   :align: center
   :alt: Comparison of effective bandwidth versus the theoretical bandwidth
-         metric in Omniperf for our simple example.
+         metric in ROCm Compute Profiler for our simple example.
   :width: 800

   Comparison of effective bandwidth versus the theoretical bandwidth
-   metric in Omniperf for our simple example.
+   metric in ROCm Compute Profiler for our simple example.

 Here we see that the theoretical bandwidth metric follows a step-function. It
 increases only when another wavefront issues an LDS instruction for up to 256
@@ -172,7 +172,7 @@ see:

 .. code-block:: shell

-   $ omniperf analyze -p workloads/lds/mi200/ -b 12.2.4 12.2.6 --dispatch 256 -n per_kernel
+   $ rocprof-compute analyze -p workloads/lds/mi200/ -b 12.2.4 12.2.6 --dispatch 256 -n per_kernel
   <...>
   --------------------------------------------------------------------------------
   12. Local Data Share (LDS)
@@ -196,7 +196,7 @@ Looking at the next ``conflicts`` dispatch (i.e., two work-items) yields:

 .. code-block:: shell

-   $ omniperf analyze -p workloads/lds/mi200/ -b 12.2.4 12.2.6 --dispatch 257 -n per_kernel
+   $ rocprof-compute analyze -p workloads/lds/mi200/ -b 12.2.4 12.2.6 --dispatch 257 -n per_kernel
   <...>
   --------------------------------------------------------------------------------
   12. Local Data Share (LDS)
@@ -4,15 +4,15 @@ Occupancy limiters example
 ==========================

 For this example, consider the
-:dev-sample:`occupancy <occupancy.hip>` included with Omniperf. We will
+:dev-sample:`occupancy <occupancy.hip>` included with ROCm Compute Profiler. We will
 investigate the use of the resource allocation panel in the
 :ref:`Workgroup Manager <desc-spi>`’s metrics section to determine occupancy
 limiters. This code contains several kernels to explore how both various
 kernel resources impact achieved occupancy, and how this is reported in
-Omniperf.
+ROCm Compute Profiler.

 This example was compiled and run on a MI250 accelerator using ROCm
-v5.6.0, and Omniperf v2.0.0:
+v5.6.0, and ROCm Compute Profiler v2.0.0:

 .. code-block:: shell

@@ -21,11 +21,11 @@ v5.6.0, and Omniperf v2.0.0:
 We have again included the ``--save-temps`` flag to get the
 corresponding assembly.

-Finally, we generate our Omniperf profile as:
+Finally, we generate our ROCm Compute Profiler profile as:

 .. code-block:: shell

-   $ omniperf profile -n occupancy --no-roof -- ./occupancy
+   $ rocprof-compute profile -n occupancy --no-roof -- ./occupancy

 .. _occupancy-experiment-design:

@@ -88,7 +88,7 @@ depend on the exact ROCm/compiler version.

 We will use various permutations of this kernel to limit occupancy, and
 more importantly for the purposes of this example, demonstrate how this
-is reported in Omniperf.
+is reported in ROCm Compute Profiler.

 .. _vgpr-occupancy:

@@ -101,7 +101,7 @@ the analyze step on this kernel:

 .. code-block:: shell

-   $ omniperf analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 --dispatch 1
+   $ rocprof-compute analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 --dispatch 1
   <...>
   --------------------------------------------------------------------------------
   0. Top Stat
@@ -226,7 +226,7 @@ Analyzing this:

 .. code-block:: shell

-   $ omniperf analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 7.1.8 --dispatch 3
+   $ rocprof-compute analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 7.1.8 --dispatch 3
   <...>
   --------------------------------------------------------------------------------
   2. System Speed-of-Light
@@ -351,7 +351,7 @@ Analyzing this workload yields:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 7.1.8 7.1.9 --dispatch 5
+   $ rocprof-compute analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 7.1.8 7.1.9 --dispatch 5
   <...>
   --------------------------------------------------------------------------------
   0. Top Stat
@@ -5,7 +5,7 @@ VALU arithmetic instruction mix

 For this example, consider the
 :dev-sample:`instruction mix sample <instmix.hip>` distributed as a part
- of Omniperf.
+ of ROCm Compute Profiler.

 .. note::

@@ -55,7 +55,7 @@ Instruction mix
 ^^^^^^^^^^^^^^^

 This example was compiled and run on a MI250 accelerator using ROCm
- v5.6.0, and Omniperf v2.0.0.
+ v5.6.0, and ROCm Compute Profiler v2.0.0.

 .. code-block:: shell

@@ -65,13 +65,13 @@ Generate the profile for this example using the following command.

 .. code-block:: shell

-   $ omniperf profile -n instmix --no-roof -- ./instmix
+   $ rocprof-compute profile -n instmix --no-roof -- ./instmix

 Analyze the instruction mix section.

 .. code-block:: shell

-   $ omniperf analyze -p workloads/instmix/mi200/ -b 10.2
+   $ rocprof-compute analyze -p workloads/instmix/mi200/ -b 10.2
   <...>
   10. Compute Units - Instruction Mix
   10.2 VALU Arithmetic Instr Mix
@@ -10,7 +10,7 @@ Global / Generic (FLAT)

 For this example, consider the
 :dev-sample:`vector memory sample <vmem.hip>` distributed as a part of
-Omniperf. This code launches many different versions of a simple
+ROCm Compute Profiler. This code launches many different versions of a simple
 read/write/atomic-only kernels targeting various address spaces. For example,
 below is our simple ``global_write`` kernel:

@@ -24,7 +24,7 @@ below is our simple ``global_write`` kernel:
 .. note::

   This example was compiled and run on an MI250 accelerator using ROCm
-   v5.6.0, and Omniperf v2.0.0.
+   v5.6.0, and ROCm Compute Profiler v2.0.0.

 .. code-block:: shell-session

@@ -34,11 +34,11 @@ We have also chosen to include the ``--save-temps`` flag to save the
 compiler temporary files, such as the generated CDNA assembly code, for
 inspection.

-Finally, we generate our ``omniperf profile`` as follows.
+Finally, we generate our ``rocprof-compute profile`` as follows.

 .. code-block:: shell-session

-   $ omniperf profile -n vmem --no-roof -- ./vmem
+   $ rocprof-compute profile -n vmem --no-roof -- ./vmem

 .. _flat-experiment-design:

@@ -94,7 +94,7 @@ First, we demonstrate our simple ``global_write`` kernel:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 1 -b 10.3 15.1.4 15.1.5 15.1.6 15.1.7 15.1.8 15.1.9 15.1.10 15.1.11  -n per_kernel
+   $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 1 -b 10.3 15.1.4 15.1.5 15.1.6 15.1.7 15.1.8 15.1.9 15.1.10 15.1.11  -n per_kernel
   <...>
   --------------------------------------------------------------------------------
   0. Top Stat
@@ -208,7 +208,7 @@ Examining this kernel in the VMEM Instruction Mix table yields:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 2 -b 10.3 -n per_kernel
+   $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 2 -b 10.3 -n per_kernel
   <...>
   0. Top Stat
   ╒════╤══════════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕
@@ -264,7 +264,7 @@ access.

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 2 -b 12.2.0 -n per_kernel
+   $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 2 -b 12.2.0 -n per_kernel
   <...>
   12. Local Data Share (LDS)
   12.2 LDS Stats
@@ -304,11 +304,11 @@ Here we observe a now familiar pattern:
  the compiler to statically eliminate, but is identically false. In this
  case, our ``main()`` function initializes the data in ``ptr`` to zero.

-Running Omniperf on this kernel yields:
+Running ROCm Compute Profiler on this kernel yields:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 3 -b 10.3 -n per_kernel
+   $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 3 -b 10.3 -n per_kernel
   <...>
   0. Top Stat
   ╒════╤════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕
@@ -383,11 +383,11 @@ false conditional (both ``zero`` and ``filter`` are set to zero in the
 kernel launch). Note that this is a *different* conditional from our
 pointer assignment (to avoid combination of the two).

-Running Omniperf on this kernel reports:
+Running ROCm Compute Profiler on this kernel reports:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 4 -b 10.3 12.2.0 16.3.10 -n per_kernel
+   $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 4 -b 10.3 12.2.0 16.3.10 -n per_kernel
   <...>
   0. Top Stat
   ╒════╤══════════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕
@@ -468,11 +468,11 @@ to a pointer.
   }


-Running Omniperf on this kernel yields:
+Running ROCm Compute Profiler on this kernel yields:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 5 -b 10.3 16.3.12 -n per_kernel
+   $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 5 -b 10.3 16.3.12 -n per_kernel
   <...>
   0. Top Stat
   ╒════╤══════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕
@@ -537,11 +537,11 @@ operation targets both LDS and global memory:
 This assigns every other work-item to atomically update global memory or
 local memory.

-Running this kernel through Omniperf shows:
+Running this kernel through ROCm Compute Profiler shows:

 .. code-block:: shell-session

-   $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 6 -b 10.3 12.2.0 16.3.12 -n per_kernel
+   $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 6 -b 10.3 12.2.0 16.3.12 -n per_kernel
   <...>
   0. Top Stat
   ╒════╤══════════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕
@@ -623,7 +623,7 @@ manner. See
 for further reading on this instruction type.

 We develop a `simple
-kernel <https://github.com/ROCm/omniperf/blob/amd-mainline/sample/stack.hip>`__
+kernel <https://github.com/ROCm/rocprofiler-compute/blob/amd-mainline/sample/stack.hip>`__
 that uses stack memory:

 .. code-block:: cpp
@@ -647,19 +647,19 @@ Our strategy here is to:
  to global memory to prevent the compiler from optimizing it out.

 This example was compiled and run on an MI250 accelerator using ROCm v5.6.0, and
-Omniperf v2.0.0.
+ROCm Compute Profiler v2.0.0.

 .. code-block:: shell-session

   $ hipcc -O3 stack.hip -o stack.hip

-And profiled using Omniperf:
+And profiled using ROCm Compute Profiler:

 .. code-block:: shell-session

-   $ omniperf profile -n stack --no-roof -- ./stack
+   $ rocprof-compute profile -n stack --no-roof -- ./stack
   <...>
-   $ omniperf analyze -p workloads/stack/mi200/  -b 10.3 16.3.11 -n per_kernel
+   $ rocprof-compute analyze -p workloads/stack/mi200/  -b 10.3 16.3.11 -n per_kernel
   <...>
   10. Compute Units - Instruction Mix
   10.3 VMEM Instr Mix
@@ -1,22 +1,23 @@
 .. meta::
-   :description: Omniperf external training resources
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD,
-              training, examples
+   :description: ROCm Compute Profiler external training resources
+   :keywords: Omniperf, examples, tutorials, videos, lesson, lessons, how

 ******************
 Learning resources
 ******************

-This section is a catalog of external resources and third-party content that
-can help you learn Omniperf. Some areas of the following content might be
-outdated.
+This section provides a curated list of external resources and third-party
+content to support learning the ROCm Compute Profiler. Some information in
+these materials may be outdated.

-Introduction to Omniperf
+ROCm Compute Profiler was previously known as Omniperf. Some of the following
+resources use the earlier name.
+
+Introduction to ROCm Compute Profiler
  :fab:`youtube` `AMD profiling workshop (Pawsey Supercomputing Research Centre) <https://www.youtube.com/watch?v=9AkxBCiInCw>`_

-Omniperf example exercises
+ROCm Compute Profiler example exercises
  `<https://github.com/amd/HPCTrainingExamples/tree/main/OmniperfExamples>`__

 AMD Instinct™ tuning guides
  :doc:`rocm:how-to/tuning-guides/mi300x/workload`
-
@@ -1,14 +1,14 @@
 .. meta::
-   :description: Omniperf: Profiling by example
-   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD
+   :description: ROCm Compute Profiler: Profiling by example
+   :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD

 ********************
 Profiling by example
 ********************

 The following examples refer to sample :doc:`HIP <hip:index>` code located in
-:fab:`github` :dev-sample:`ROCm/omniperf/blob/amd-mainline/sample <>` and distributed
-as part of Omniperf.
+:fab:`github` :dev-sample:`ROCm/rocprofiler-compute/blob/amd-mainline/sample <>`
+and distributed as part of ROCm Compute Profiler.

 .. include:: ./includes/valu-arithmetic-instruction-mix.rst

@@ -1,33 +1,33 @@
 .. meta::
-   :description: What is Omniperf?
+   :description: What is ROCm Compute Profiler?
   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD

-*****************
-What is Omniperf?
-*****************
+******************************
+What is ROCm Compute Profiler?
+******************************

-Omniperf is a kernel-level profiling tool for machine learning and high
+ROCm Compute Profiler is a kernel-level profiling tool for machine learning and high
 performance computing (HPC) workloads running on AMD Instinct™ accelerators.

 AMD Instinct MI-series accelerators are data center-class GPUs designed for
-compute and have some graphics capabilities disabled or removed. Omniperf
-primarily targets use with
+compute and have some graphics capabilities disabled or removed.
+ROCm Compute Profiler primarily targets use with
 :doc:`accelerators in the MI300, MI200, and MI100 families <rocm:conceptual/gpu-arch>`.
 Development is in progress to support Radeon™ (RDNA) GPUs.

-Omniperf is built on top of :doc:`ROCProfiler <rocprofiler:rocprofv1>` to
+ROCm Compute Profiler is built on top of :doc:`ROCProfiler <rocprofiler:rocprofv1>` to
 monitor hardware performance counters.

 .. _high-level-design:

-High-level design of Omniperf
-=============================
+High-level design
+=================

-The architecture of Omniperf consists of three major components shown in the
+The architecture of ROCm Compute Profiler consists of three major components shown in the
 following diagram.

-Core Omniperf profiler
----------------------
+Core ROCm Compute Profiler
+--------------------------

 Acquires raw performance counters via application replay using ``rocprof``.
 Counters are stored in a comma-separated-values format for further
@@ -35,43 +35,43 @@ Counters are stored in a comma-separated-values format for further
 micro-benchmarks to acquire hierarchical roofline data. The roofline model is
 not available on accelerators pre-MI200.

-Grafana server for Omniperf
---------------------------
+Grafana server for ROCm Compute Profiler
+----------------------------------------

 * **Grafana database import**: All raw performance counters are imported into
  a :ref:`backend MongoDB database <grafana-mongodb-setup>` to support
  analysis and visualization in the Grafana GUI. Compatibility with
-  previously generated data using older Omniperf versions is not guaranteed.
+  previously generated data using older ROCm Compute Profiler versions is not guaranteed.

 * **Grafana analysis dashboard GUI**: The
  :doc:`Grafana dashboard <how-to/analyze/grafana-gui>` retrieves the raw
  counters information from the backend database. It displays the relevant
  performance metrics and visualization.

-Omniperf standalone GUI analyzer
--------------------------------
+ROCm Compute Profiler standalone GUI analyzer
+---------------------------------------------

-Omniperf provides a :doc:`standalone GUI <how-to/analyze/standalone-gui>` to
+ROCm Compute Profiler provides a :doc:`standalone GUI <how-to/analyze/standalone-gui>` to
 enable basic performance analysis without the need to import data into a
 database instance. Find setup instructions in :doc:`install/grafana-setup`

 .. image:: data/install/omniperf_server_vs_client_install.png
   :align: center
-   :alt: Architectural design of Omniperf
+   :alt: Architectural design of ROCm Compute Profiler
   :width: 800

-Omniperf features
-=================
+Features
+========

-Omniperf offers comprehensive profiling based on all available hardware counters
+ROCm Compute Profiler offers comprehensive profiling based on all available hardware counters
 for the target accelerator. It delivers advanced performance analysis features,
 such as system Speed-of-Light (SOL) and hardware block-level SOL evaluations.
-Additionally, Omniperf provides in-depth memory chart analysis, roofline
+Additionally, ROCm Compute Profiler provides in-depth memory chart analysis, roofline
 analysis, baseline comparisons, and more, ensuring a thorough understanding of
 system performance.

-Omniperf supports analysis through both the :doc:`command line </how-to/analyze/cli>` or a
-:doc:`GUI </how-to/analyze/grafana-gui>`. The following list describes Omniperf's features at a
+ROCm Compute Profiler supports analysis through both the :doc:`command line </how-to/analyze/cli>` or a
+:doc:`GUI </how-to/analyze/grafana-gui>`. The following list describes ROCm Compute Profiler's features at a
 high level.

 * :doc:`Support for AMD Instinct MI300, MI200, and MI100 accelerators <reference/compatible-accelerators>`
@@ -107,8 +107,8 @@ high level.

  * :ref:`Scalar L1D Cache panel <grafana-panel-sl1d-cache>`

-  * :ref:`L1 Address Processing Unit, or, Texture Addresser (TA) <grafana-panel-ta>`
-    and :ref:`L1 Backend Data Processing Unit, or, Texture Data (TD) <grafana-panel-td>` panels
+  * :ref:`L1 Address Processing Unit or Texture Addresser (TA) <grafana-panel-ta>`;
+    and :ref:`L1 Backend Data Processing Unit or Texture Data (TD) <grafana-panel-td>` panels

  * :ref:`Vector L1D Cache panel <grafana-panel-vl1d>`

@@ -1 +1 @@
-/dashboards
+/dashboards
--- a/Показать больше
+++ b/Показать больше