Documentation Updates (#470)

* Updating installation doc

* updating README

* Addressing Yifan's feedback

* trivial updates

* Added limitation for individual xcc in readme

* Added rocprofv3 page

* README updates

* Updating rocprofv3

* source formatting (clang-format v11) (#538)

Co-authored-by: bgopesh <7112102+bgopesh@users.noreply.github.com>

* Merging documentation team's update

* Update source/docs/installation.md

Co-authored-by: Jonathan R. Madsen <jrmadsen@users.noreply.github.com>

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: bgopesh <7112102+bgopesh@users.noreply.github.com>
Co-authored-by: Jonathan R. Madsen <jrmadsen@users.noreply.github.com>

[ROCm/rocprofiler-sdk commit: 665c546e65]
Cette révision appartient à :
Gopesh Bhardwaj
2024-03-08 08:35:16 +05:30
révisé par GitHub
Parent d820cf3018
révision 1295c42022
12 fichiers modifiés avec 581 ajouts et 57 suppressions
+67 -1
Voir le fichier
@@ -1 +1,67 @@
# rocprofiler-sdk-internal
# ROCprofiler-SDK: Application Profiling, Tracing, and Performance Analysis
***
Note: rocprofiler-sdk is currently `not` supported as part of public ROCm software stack and only distributed as a beta
release to customers.
***
## Overview
ROCProfiler-SDK is AMD’s new and improved tooling infrastructure that provides a hardware specific low level performance analysis interface for the profiling and the tracing of GPU compute applications. To see whats changed [Click Here](https://github.com/ROCm/rocprofiler-sdk-internal/blob/main/source/docs/about.md)
## GPU Metrics
- GPU hardware counters
- HIP API tracing
- HIP kernel tracing
- HSA API tracing
- HSA operation tracing
- Marker(ROCtx) tracing
## Tool Support
rocprofv3 is the command line tool that is built using rocprofiler-sdk library and shipped with ROCm stack. To see details on
the command line options of rocprofv3, please see rocprofv3 user guide
[Click Here](https://github.com/ROCm/rocprofiler-sdk-internal/blob/main/source/docs/rocprofv3.md)
## Documentation
We make use of doxygen to automatically generate API documentation. Generated document can be found in the following path:
``` bash
<ROCM_PATH>/share/html/rocprofiler-sdk
```
ROCM_PATH by default is /opt/rocm
It can be set by the user in different location if needed.
## Build and Installation
```bash
git clone https://git@github.com:ROCm/rocprofiler-sdk-internal.git rocprofiler-sdk-source
cmake \
-B rocprofiler-sdk-build \
-D ROCPROFILER_BUILD_TESTS=ON \
-D ROCPROFILER_BUILD_SAMPLES=ON \
-D ROCPROFILER_BUILD_DOCS=ON \
-D CMAKE_INSTALL_PREFIX=/opt/rocm \
rocprofiler-sdk-source
cmake --build rocprofiler-sdk-build --target all --parallel 8
```
To install ROCprofiler, run:
```bash
cmake --build rocprofiler-sdk-build --target install
```
Please see detailed section on build and installation here: [click](https://github.com/ROCm/rocprofiler-sdk-internal/blob/main/source/docs/about.md)
## Support
Please report in the Github Issues.
## Limitations
- Individual xcc mode is not supported.
+19
Voir le fichier
@@ -0,0 +1,19 @@
# Buffered Services
For the buffered approach, supported buffer record categories are enumerated in `rocprofiler_buffer_category_t` category field.
## Buffered Tracing Services
```eval_rst
.. toctree::
:glob:
:maxdepth: 4
```
## Overview
In buffered approach, callbacks are receieved for batches of records from an internal (background) thread. Supported buffered tracing services are enumerated in `rocprofiler_buffer_tracing_kind_t`.
## HSA API Tracing
## Kernel Tracing
-14
Voir le fichier
@@ -1,14 +0,0 @@
# Buffered Tracing Services
```eval_rst
.. toctree::
:glob:
:maxdepth: 4
```
## Overview
## HSA API Tracing
## Kernel Tracing
+4 -3
Voir le fichier
@@ -10,9 +10,10 @@
features
installation
tool_library_overview
callback_tracing
buffered_tracing
callback_services
buffered_services
intercept_table
developer_api
getting_started
samples
rocprofv3
```
+38 -9
Voir le fichier
@@ -6,13 +6,16 @@
:maxdepth: 4
```
## Quick Start (Latest Release, Binary Installer)
TODO: Installation quick start
## Operating System
TODO: supported OSes
ROCprofiler is only supported on Linux. The following distributions are tested:
- Ubuntu 20.04
- Ubuntu 22.04
- OpenSUSE 15.4
- RedHat 8.8
Other OS distributions may be supported but are not tested.
### Identifying the Operating System
@@ -35,16 +38,42 @@ The relevent fields are `ID` and the `VERSION_ID`.
### Build Requirements
TODO: build reqs
ROCprofiler needs a CMake (https://cmake.org/) version 3.21 or higher.
***If the system installed cmake is too old, installing a new version of cmake can be done through several methods. One of the easiest options is to use PyPi (i.e. python’s pip):***
```bash
pip install --user 'cmake==3.21.0'
export PATH=${HOME}/.local/bin:${PATH}
```
### Building ROCprofiler
TODO: cmake build
```bash
git clone https://git@github.com:ROCm/rocprofiler-sdk-internal.git rocprofiler-sdk-source
cmake \
-B rocprofiler-sdk-build \
-D ROCPROFILER_BUILD_TESTS=ON \
-D ROCPROFILER_BUILD_SAMPLES=ON \
-D ROCPROFILER_BUILD_DOCS=ON \
-D CMAKE_INSTALL_PREFIX=/opt/rocm \
rocprofiler-sdk-source
cmake --build rocprofiler-sdk-build --target all --parallel 8
```
### Testing ROCprofiler
TODO: ctest
To run the built tests, cd into the `rocprofiler-sdk-build` directory and run:
```bash
ctest --output-on-failure -O ctest.all.log
```
### Installing ROCprofiler
TODO: `make install` and/or `cpack`
To install ROCprofiler from the `rocprofiler-sdk-build` directory, run:
```bash
cmake --build rocprofiler-sdk-build --target install
```
+437
Voir le fichier
@@ -0,0 +1,437 @@
# rocprofv3 user guide
ROCProfiler SDK is a tooling infrastructure designed for profiling general-purpose GPU compute applications running on the ROCm platform. It supports application tracing to provide a big picture of the GPU application execution and kernel profiling to provide low-level hardware details from the performance counters.
The ROCProfiler SDK library provides runtime-independent APIs for tracing runtime calls and asynchronous activities such as GPU kernel dispatches and memory moves. The tracing includes callback APIs for runtime API tracing and activity APIs for asynchronous activity records logging. You can utilize these APIs to develop a tracing tool or to implement tracing in the application.
In this document, we discuss the command-line tool `rocprofv3` in detail, which is based on the APIs from the ROCProfiler SDK library.
## Installation
To install ROCProfiler SDK from source, follow the instructions provided in the sections below:
### Prerequisites
- Linux operating system. Here is the list of operating systems tested for ROCProfiler SDK support:
- Ubuntu 20.04
- Ubuntu 22.04
- OpenSUSE 15.4
- RedHat 8.8
To check a system’s operating system and version, see the `/etc/os-release` and `/usr/lib/os-release` files:
```bash
$ cat /etc/os-release
NAME="Ubuntu"
VERSION="20.04.4 LTS (Focal Fossa)"
ID=ubuntu
...
VERSION_ID="20.04"
...
```
- Cmake version 3.21 or higher.
- To install a new version of Cmake, we recommend using PyPi (Python’s pip):
```bash
pip install --user 'cmake==3.21.0'
export PATH=${HOME}/.local/bin:${PATH}
```
### Build
To build ROCProfiler SDK, use:
```bash
git clone https://git@github.com:ROCm/rocprofiler-sdk-internal.git rocprofiler-sdk-source
```
```bash
cmake --build rocprofiler-sdk-build --target all --parallel 8
```
To see the various build options along with their default values, use:
```bash
$ cmake -LA
REPRODUCIBLE_RUNTIME_USE_MPI:BOOL=OFF
ROCPROFILER_BLACK_FORMAT_EXE:FILEPATH=ROCPROFILER_BLACK_FORMAT_EXE-NOTFOUND
ROCPROFILER_BUILD_CI:BOOL=OFF
ROCPROFILER_BUILD_CODECOV:BOOL=OFF
ROCPROFILER_BUILD_DEBUG:BOOL=OFF
ROCPROFILER_BUILD_DEVELOPER:BOOL=OFF
ROCPROFILER_BUILD_DOCS:BOOL=OFF
ROCPROFILER_BUILD_FMT:BOOL=ON
ROCPROFILER_BUILD_GHC_FS:BOOL=ON
ROCPROFILER_BUILD_GLOG:BOOL=ON
ROCPROFILER_BUILD_GTEST:BOOL=ON
ROCPROFILER_BUILD_RELEASE:BOOL=OFF
ROCPROFILER_BUILD_SAMPLES:BOOL=OFF
ROCPROFILER_BUILD_STACK_PROTECTOR:BOOL=ON
ROCPROFILER_BUILD_STATIC_LIBGCC:BOOL=OFF
ROCPROFILER_BUILD_STATIC_LIBSTDCXX:BOOL=OFF
ROCPROFILER_BUILD_TESTS:BOOL=ON
ROCPROFILER_BUILD_WERROR:BOOL=OFF
ROCPROFILER_CLANG_FORMAT_EXE:FILEPATH=ROCPROFILER_CLANG_FORMAT_EXE-NOTFOUND
ROCPROFILER_CLANG_TIDY_COMMAND:FILEPATH=ROCPROFILER_CLANG_TIDY_COMMAND-NOTFOUND
ROCPROFILER_CMAKE_FORMAT_EXE:FILEPATH=ROCPROFILER_CMAKE_FORMAT_EXE-NOTFOUND
ROCPROFILER_CPACK_SYSTEM_NAME:STRING=Linux
ROCPROFILER_DEBUG_TRACE:BOOL=OFF
ROCPROFILER_DEFAULT_ROCM_PATH:PATH=/opt/rocm-6.1.0-13278
ROCPROFILER_ENABLE_CLANG_TIDY:BOOL=OFF
ROCPROFILER_LD_AQLPROFILE:BOOL=OFF
ROCPROFILER_MEMCHECK:STRING=
ROCPROFILER_REGENERATE_COUNTERS_PARSER:BOOL=OFF
ROCPROFILER_UNSAFE_NO_VERSION_CHECK:BOOL=OFF
```
### Install
To install ROCProfiler SDK from the `rocprofiler-sdk-build` directory, run:
```bash
cmake --build rocprofiler-sdk-build --target install
```
### Test
To run the build tests, `cd` into the `rocprofiler-sdk-build` directory and run:
```bash
ctest -R
```
## Usage
`rocprofv3` is a CLI tool that helps you to quickly optimize the applications and understand the low-level kernel details without requiring any modification in the source code. `rocprofv3` is being developed to be backward compatible with its predecessor `rocprof` along with providing more features to help users profile their applications with better accuracy.
The usage of `rocprofv3` for application tracing and kernel profiling using various command-line options is demonstrated in the following sections.
`rocprofv3` is installed with ROCm under `/opt/rocm/bin`. To use the tool from anywhere in the system, export `PATH` variable:
```bash
export PATH=$PATH:/opt/rocm/bin
```
Before you can start tracing or profiling your HIP application using `rocprofv3`, build the application using:
```bash
cmake -B <build-directory> <source-directory> -DCMAKE_PREFIX_PATH=/opt/rocm
cmake --build <build-directory> --target all --parallel <N>
```
### Options
Below is the list of `rocprofv3` command-line options. Some options are used for application tracing and some for kernel profiling while the output control options control the presentation and redirection of the generated output.
| Option | Description | Use |
|--------|-------------|-----|
| -d \| --output-directory | Specifies the path for the output files. | Output control |
| --hip-trace | Collects HIP runtime traces. | Application tracing |
| --hip-compiler-trace | Collects HIP compiler generated code traces. | Application tracing |
| --hsa-trace | Collects HSA API trace. | Application tracing |
| -i | Specifies the input file. | Kernel profiling |
| --kernel-trace | Collects kernel dispatch traces. | Application tracing |
| -M \| --mangled-kernels | Overrides the default demangling of kernel names. | Output control |
| --marker-trace | Collects marker (ROC-TX) traces. | Application tracing |
| --memory-copy-trace | Collects memory copy traces. | Application tracing |
| -o \| --output-file | Specifies the name of the output file. Note that this name is appended to the default names (_api_trace or counter_collection.csv) of the generated files. | Output control |
| --sys-trace | Collects HIP, HSA, memory copy, marker, and kernel dispatch traces. | Application Tracing |
| -T \| --truncate-kernels | Truncates the demangled kernel names for improved readability. | Output control |
You can also see all the `rocprofv3` options using:
```bash
rocprofv3 --help
```
### Application tracing
Application tracing provides the big picture of a program’s execution by collecting data on the execution times of API calls and GPU commands, such as kernel execution, async memory copy, and barrier packets. This information can be used as the first step in the profiling process to answer important questions, such as how much percentage of time was spent on memory copy and which kernel took the longest time to execute.
To use `rocprofv3` for application tracing, run:
```bash
rocprofv3 <tracing_option> <app_relative_path>
```
#### HIP trace
HIP trace comprises of execution traces for the entire application at the HIP level. This includes HIP API functions and their asynchronous activities at the runtime level. In general, HIP APIs directly interact with the user program. It is easier to analyze HIP traces as you can directly map the traces to the program.
To trace HIP runtime APIs, use:
```bash
rocprofv3 --hip-trace < app_relative_path >
```
Running the above command generates a `hip_api_trace.csv` file prefixed with the process Id.
```bash
$ cat 238_hip_api_trace.csv
"Domain","Function","Process_Id","Thread_Id","Correlation_Id","Start_Timestamp","End_Timestamp"
"HIP_RUNTIME_API","hipGetDevicePropertiesR0600",238,238,1,1191915574691984,1191915687784011
"HIP_RUNTIME_API","hipMalloc",238,238,2,1191915691312459,1191915691388696
"HIP_RUNTIME_API","hipMalloc",238,238,3,1191915691390637,1191915691423279
"HIP_RUNTIME_API","hipMemcpy",238,238,4,1191915691439107,1191916547828448
"HIP_RUNTIME_API","hipLaunchKernel",238,238,5,1191916547842972,1191916548408842
"HIP_RUNTIME_API","hipMemcpy",238,238,6,1191916548412677,1191916550217834
"HIP_RUNTIME_API","hipFree",238,238,7,1191916562618151,1191916562789093
"HIP_RUNTIME_API","hipFree",238,238,8,1191916562790923,1191916562836351
```
To trace HIP compile time APIs, use:
```bash
rocprofv3 --hip-compiler-trace < app_relative_path >
```
Running the above command generates a `hip_api_trace.csv` file prefixed with the process Id.
```bash
$ cat 208_hip_api_trace.csv
"Domain","Function","Process_Id","Thread_Id","Correlation_Id","Start_Timestamp","End_Timestamp"
"HIP_COMPILER_API","__hipRegisterFatBinary",208,208,1,1508780270085955,1508780270096795
"HIP_COMPILER_API","__hipRegisterFunction",208,208,2,1508780270104242,1508780270115355
"HIP_COMPILER_API","__hipPushCallConfiguration",208,208,3,1508780613897816,1508780613898701
"HIP_COMPILER_API","__hipPopCallConfiguration",208,208,4,1508780613901714,1508780613902200
```
For the description of the fields in the output file, see [Output file fields](#output-file-fields).
#### HSA trace
The HIP runtime library is implemented with the low-level HSA runtime. HSA API tracing is more suited for advanced users who want to understand the application behavior at the lower level. In general, tracing at the HIP-level is recommended for most users. You are advised to use HSA trace only if you are familiar with HSA runtime.
HSA trace contains the start and end time of HSA runtime API calls and their asynchronous activities.
```bash
rocprofv3 --hsa-trace < app_relative_path >
```
Running the above command generates `hsa_api_trace.csv` file prefixed with process Id. Note that the contents of this file have been truncated for demonstration purposes.
```bash
$ cat 197_hsa_api_trace.csv
"Domain","Function","Process_Id","Thread_Id","Correlation_Id","Start_Timestamp","End_Timestamp"
"HSA_CORE_API","hsa_system_get_major_extension_table",197,197,1,1507843974724237,1507843974724947
"HSA_CORE_API","hsa_agent_get_info",197,197,3,1507843974754471,1507843974755014
"HSA_AMD_EXT_API","hsa_amd_memory_pool_get_info",197,197,5,1507843974761705,1507843974762398
"HSA_AMD_EXT_API","hsa_amd_memory_pool_get_info",197,197,6,1507843974763901,1507843974764030
"HSA_AMD_EXT_API","hsa_amd_memory_pool_get_info",197,197,7,1507843974765121,1507843974765224
"HSA_AMD_EXT_API","hsa_amd_memory_pool_get_info",197,197,8,1507843974766196,1507843974766328
"HSA_AMD_EXT_API","hsa_amd_memory_pool_get_info",197,197,9,1507843974767534,1507843974767641
"HSA_AMD_EXT_API","hsa_amd_memory_pool_get_info",197,197,10,1507843974768639,1507843974768779
"HSA_AMD_EXT_API","hsa_amd_agent_iterate_memory_pools",197,197,4,1507843974758768,1507843974769238
"HSA_CORE_API","hsa_agent_get_info",197,197,11,1507843974771091,1507843974771537
```
For the description of the fields in the output file, see [Output file fields](#output-file-fields).
#### Marker trace
In certain situations, such as debugging performance issues in large-scale GPU programs, API-level tracing may be too fine-grained to provide a big picture of the program execution. In such cases, it is helpful to define specific tasks to be traced.
To specify the tasks for tracing, enclose the respective source code with the API calls provided by `ROC-TX` library. This process is also known as instrumentation. As the scope of code for instrumentation is defined using the enclosing API calls, it is called a range. A range is a programmer-defined task that has a well-defined start and end code scope. You can also fine grain the scope specified within a range using further nested ranges. The `rocprofv3` tool also reports the timelines for these nested ranges.
Here is a list of useful APIs for code instrumentation.
- `roctxMark`: Inserts a marker in the code with a message. Creating marks can help you see when a line of code is executed.
- `roctxRangeStart`: Starts a range. Ranges can be started by different threads.
- `roctxRangePush`: Starts a new nested range.
- `roctxRangePop`: Stops the current nested range.
- `roctxRangeStop`: Stops the given range.
See how to use `rocTX` APIs in the MatrixTranspose application below:
```bash
roctxMark("before hipLaunchKernel");
int rangeId = roctxRangeStart("hipLaunchKernel range");
roctxRangePush("hipLaunchKernel");
// Lauching kernel from host
hipLaunchKernelGGL(matrixTranspose, dim3(WIDTH/THREADS_PER_BLOCK_X, WIDTH/THREADS_PER_BLOCK_Y), dim3(THREADS_PER_BLOCK_X, THREADS_PER_BLOCK_Y), 0,0,gpuTransposeMatrix,gpuMatrix, WIDTH);
roctxMark("after hipLaunchKernel");
// Memory transfer from device to host
roctxRangePush("hipMemcpy");
hipMemcpy(TransposeMatrix, gpuTransposeMatrix, NUM * sizeof(float), hipMemcpyDeviceToHost);
roctxRangePop(); // for "hipMemcpy"
roctxRangePop(); // for "hipLaunchKernel"
roctxRangeStop(rangeId);
```
To trace the API calls enclosed within the range, use:
```bash
rocprofv3 --marker-trace < app_relative_path >
```
Running the above command generates `marker_api_trace.csv` file prefixed with the process Id.
```bash
$ cat 210_marker_api_trace.csv
"Domain","Function","Process_Id","Thread_Id","Correlation_Id","Start_Timestamp","End_Timestamp"
"MARKER_CORE_API","before hipLaunchKernel",717,717,1,1520113899312225,1520113899312225
"MARKER_CORE_API","after hipLaunchKernel",717,717,4,1520113900128482,1520113900128482
"MARKER_CORE_API","hipMemcpy",717,717,5,1520113900141100,1520113901483408
"MARKER_CORE_API","hipLaunchKernel",717,717,3,1520113899684965,1520113901491622
"MARKER_CORE_API","hipLaunchKernel range",717,0,2,1520113899682208,1520113901495882
```
For the description of the fields in the output file, see [Output file fields](#output-file-fields).
#### Kernel trace
To trace kernel dispatch traces, use:
```bash
rocprofv3 --kernel-trace < app_relative_path >
```
Running the above command generates `kernel_trace.csv` file prefixed with the process Id.
```bash
$ cat 199_kernel_trace.csv
"Kind","Agent_Id","Queue_Id","Kernel_Id","Kernel_Name","Correlation_Id","Start_Timestamp","End_Timestamp","Private_Segment_Size","Group_Segment_Size","Workgroup_Size_X","Workgroup_Size_Y","Workgroup_Size_Z","Grid_Size_X","Grid_Size_Y","Grid_Size_Z"
"KERNEL_DISPATCH",1,139690710949888,15,"matrixTranspose(float*, float*, int)",0,671599758568,671599825328,0,0,4,4,1,1024,1024,1
```
For the description of the fields in the output file, see [Output file fields](#output-file-fields).
#### Memory copy trace
To trace memory moves across the application, use:
```bash
rocprofv3 –-memory-copy-trace < app_relative_path >
```
Running the above command generates `memory_copy_trace.csv` file prefixed with the process Id.
```bash
$ cat 197_memory_copy_trace.csv
"Kind","Direction","Source_Agent_Id","Destination_Agent_Id","Correlation_Id","Start_Timestamp","End_Timestamp"
"MEMORY_COPY","HOST_TO_DEVICE",0,1,0,14955949675563,14955950239443
"MEMORY_COPY","DEVICE_TO_HOST",1,0,0,14955952733485,14955953315285
```
For the description of the fields in the output file, see [Output file fields](#output-file-fields).
#### Sys trace
This is an all-inclusive option to collect all the above-mentioned traces.
```bash
rocprofv3 –-sys-trace < app_relative_path >
```
Running the above command generates `hip_api_trace.csv`, `hsa_api_trace.csv`, `kernel_trace.csv`, `memory_copy_trace.csv`, and `marker_api_trace.csv` (if `rocTX` APIs are specified in the application) files prefixed with the process Id.
### Kernel profiling
The application tracing functionality allows you to evaluate the duration of kernel execution but is of little help in providing insight into kernel execution details. The kernel profiling functionality allows you to select kernels for profiling and choose the basic counters or derived metrics to be collected for each kernel execution, thus providing a greater insight into kernel execution.
For more information on counters available on MI200, refer to the [MI200 Performance Counters and Metrics](https://rocm.docs.amd.com/en/latest/conceptual/gpu-arch/mi300-mi200-performance-counters.html).
#### Input file
To collect the desired basic counters or derived metrics, mention them in an input file as shown below. The line consisting of the counter or metric names must begin with `pmc`.
```bash
$ cat input.txt
pmc: GPUBusy SQ_WAVES
pmc: GRBM_GUI_ACTIVE
```
The number of basic counters or derived metrics that can be collected in one run of profiling is limited by the GPU hardware resources. If too many counters or metrics are selected, the kernels need to be executed multiple times to collect the counters or metrics. For multi-pass execution, include multiple rows of `pmc` in the input file. Counters or metrics in each `pmc` row can be collected in each run of the kernel.
#### Kernel profiling output
To supply the input file for kernel profiling, use:
```bash
rocprofv3 -i input.txt <app_relative_path>
```
Running the above command generates `./pmc_n/counter_collection.csv` file prefixed with the process Id. For each `pmc` row, a directory `pmc_n` containing a `counter_collection.csv` file is generated where n = 1 for the first row and so on.
Each row of the CSV file is an instance of kernel execution. Here is a truncated version of the output file from `pmc_1`.
```bash
$ cat pmc_1/218_counter_collection.csv
"Counter_Id","Agent_Id","Queue_Id","Process_Id","Thread_Id","Grid_Size","Kernel-Name","Workgroup_Size","LDS_Block_Size","Scratch_Size","VGPR_Count","SGPR_Count","Counter_Name","Counter_Value"
365,1,139713210765312,239,239,1048576,"matrixTranspose(float*, float*, int)",16,0,0,8,128,"SQ_WAVES[0]",1404
365,1,139713210765312,239,239,1048576,"matrixTranspose(float*, float*, int)",16,0,0,8,128,"SQ_WAVES[64]",1336
365,1,139713210765312,239,239,1048576,"matrixTranspose(float*, float*, int)",16,0,0,8,128,"SQ_WAVES[128]",1401
365,1,139713210765312,239,239,1048576,"matrixTranspose(float*, float*, int)",16,0,0,8,128,"SQ_WAVES[192]",1323
365,1,139713210765312,239,239,1048576,"matrixTranspose(float*, float*, int)",16,0,0,8,128,"SQ_WAVES[256]",1402
365,1,139713210765312,239,239,1048576,"matrixTranspose(float*, float*, int)",16,0,0,8,128,"SQ_WAVES[320]",1396
```
### Output file fields
The various fields or the columns in the output CSV files generated for application tracing and kernel profiling are described here:
| Field | Description |
|-------|-------------|
| Agent_Id | GPU identifier to which the kernel was submitted. |
| Correlation_Id | Unique identifier for correlation between HIP and HSA async calls during activity tracing. |
| Start_Timestamp | Begin time in nanoseconds (`ns`) when the kernel begins execution. |
| End_Timestamp | End time in ns when the kernel finishes execution. |
| Queue_Id | ROCm queue unique identifier to which the kernel was submitted. |
| Private_Segment_Size | The amount of memory required for the combined private, spill and arg segments for a work-item in bytes. |
| Group_Segment_Size | The amount of group segment memory required by a workgroup in bytes. This does not include any dynamically allocated group segment memory that may be added when the kernel is dispatched. |
| Workgroup_Size | Size of the workgroup as declared by the compute shader. |
| Workgroup_Size_n | Size of the workgroup in the nth dimension as declared by the compute shader, where n = X, Y, or Z. |
| Grid_Size | Number of thread blocks required to launch the kernel. |
| Grid_Size_n | Number of thread blocks in the nth dimension required to launch the kernel, where n = X, Y, or Z. |
| LDS_Block_Size | Thread block size for the kernel's Local Data Share (`LDS`) memory. |
| Scratch_Size | Kernel’s scratch memory size. |
| SGPR_Count | Kernel's Scalar General-Purpose Register (`SGPR`) count. |
| VGPR_Count | Kernel's Vector General-Purpose Register (`VGPR`) count. |
### Sample programs
After the ROCm build is installed:
- Sample programs are installed here:
```bash
/opt/rocm/share/rocprofiler-sdk/samples
```
- `rocprofv3` tool is installed here:
```bash
/opt/rocm/bin
```
To build samples from any directory, run:
```bash
cmake -B <build directory> /opt/rocm/share/rocprofiler-sdk/samples -DCMAKE_PREFIX_PATH=/opt/rocm
cmake --build <build directory> --target all --parallel 8
```
To run the built samples, `cd` into the `<build directory>` mentioned in the build commands above and run:
```bash
ctest -V
```
@@ -1,4 +1,6 @@
## Running Samples and Tool
# Samples
## Running Samples
```eval_rst
.. toctree::
@@ -34,23 +36,3 @@ To run the built samples, cd into the `build-rocprofiler-sdk-samples` directory
```bash
ctest -V
### Running Tool
#### Build an HIP application:
```bash
cmake -B <build-directory> <source-directory> -DCMAKE_PREFIX_PATH=/opt/rocm
cmake --build <build-directory> --target all --parallel <N>
```
#### Run the Tool:
```bash
rocprofv3 --hsa-api ./MatrixTranspose
```
See more tool options with
```bash
rocprofv3 --help
```
+1 -1
Voir le fichier
@@ -1,4 +1,4 @@
# Building Tool Library
# Tool Library
```eval_rst
.. toctree::
+1 -1
Voir le fichier
@@ -98,7 +98,7 @@ typedef struct rocprofiler_agent_mem_bank_t
} rocprofiler_agent_mem_bank_t;
/**
* @brief Agent.
* @brief Agent (rocprofiler_agent_t stores the properties of an Agent)
*/
typedef struct rocprofiler_agent_v0_t
{
+3 -1
Voir le fichier
@@ -305,7 +305,9 @@ typedef uint64_t rocprofiler_thread_id_t;
/**
* @brief Tracing Operation ID. Depending on the kind, operations can be determined.
* If the value is equal to zero that means all operations will be considered
* for tracing.
* for tracing. Detailed API tracing operations can be found at associated header file
* for that partiular operation. i.e: For ROCProfiler enumeration of HSA AMD Extended API tracing
* operations, look at source/include/rocprofiler-sdk/hsa/amd_ext_api_id.h
*/
typedef uint32_t rocprofiler_tracing_operation_t;
+8 -6
Voir le fichier
@@ -35,12 +35,14 @@ ROCPROFILER_EXTERN_C_INIT
*/
/**
* @brief A pointer to this data structure is provided to the client tool initialization function.
* The name member can be set by the client to assist with debugging (e.g. rocprofiler cannot start
* your context because there is a conflicting context started by `<name>` -- at least that is the
* plan). The handle member is a unique identifer assigned by rocprofiler for the client and the
* client can store it and pass it to the @ref rocprofiler_client_finalize_t function to force
* finalization (i.e. deactivate all of it's contexts) for the client.
* @brief A client refers to an individual or entity engaged in the configuration of ROCprofiler
* services. e.g: any third party tool like PAPI or any internal tool (Omnitrace). A pointer to this
* data structure is provided to the client tool initialization function. The name member can be set
* by the client to assist with debugging (e.g. rocprofiler cannot start your context because there
* is a conflicting context started by `<name>` -- at least that is the plan). The handle member is
* a unique identifer assigned by rocprofiler for the client and the client can store it and pass it
* to the @ref rocprofiler_client_finalize_t function to force finalization (i.e. deactivate all of
* it's contexts) for the client.
*/
typedef struct
{