Jonathan R. Madsen
ea282d9301
* v1.3.0 * ROCm 5.2 and extensions tweaks * Container workflow + miscellaneous updates * Misc fixes + timemory submodule update - timemory submodule update for multiple definitions of variant_apply * Increase timeouts * Remove obsolete Julia docs and script - support for rocprofiler makes rocprof merging obsolete * Fix cpack testing and combine cpack workflows into single script * Install components + omnitrace tpl exes - Improved COMPONENT specification for installs - Install PAPI executables with omnitrace- prefix and hyphens - Install Perfetto executables with omnitrace- prefix and hyphens * Update docs on perfetto and papi command-line tools * remove ubuntu 22.04 from containers workflow * remove containers workflow running on all pushes * Fix CI_SCRIPT_ARGS * Fix PAPI utils install * Fixed traced test in workflow + removed return char - validate-perfetto-proto.py had return character * Fix test-docker-release.sh script to use correct container * Release build bc RelWtihDebInfo using too much memory
237 líneas
9.2 KiB
Markdown
Archivo Ejecutable
237 líneas
9.2 KiB
Markdown
Archivo Ejecutable
# Omnitrace: Application Profiling, Tracing, and Analysis
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[](https://github.com/AMDResearch/omnitrace/actions/workflows/ubuntu-bionic.yml)
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[](https://github.com/AMDResearch/omnitrace/actions/workflows/ubuntu-focal.yml)
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[](https://github.com/AMDResearch/omnitrace/actions/workflows/opensuse.yml)
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> ***[Omnitrace](https://github.com/AMDResearch/omnitrace) is an AMD open source research project and is not supported as part of the ROCm software stack.***
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## Overview
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AMD Research is seeking to improve observability and performance analysis for software running on AMD heterogeneous systems.
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If you are familiar with [rocprof](https://rocmdocs.amd.com/en/latest/ROCm_Tools/ROCm-Tools.html) and/or [uProf](https://developer.amd.com/amd-uprof/),
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you will find many of the capabilities of these tools available via Omnitrace in addition to many new capabilities.
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Omnitrace is a comprehensive profiling and tracing tool for parallel applications written in C, C++, Fortran, HIP, OpenCL, and Python which execute on the CPU or CPU+GPU.
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It is capable of gathering the performance information of functions through any combination of binary instrumentation, call-stack sampling, user-defined regions, and Python interpreter hooks.
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Omnitrace supports interactive visualization of comprehensive traces in the web browser in addition to high-level summary profiles with mean/min/max/stddev statistics.
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In addition to runtimes, omnitrace supports the collection of system-level metrics such as the CPU frequency, GPU temperature, and GPU utilization, process-level metrics
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such as the memory usage, page-faults, and context-switches, and thread-level metrics such as memory usage, CPU time, and numerous hardware counters.
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### Data Collection Modes
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- Dynamic instrumentation
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- Runtime instrumentation
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- Instrument executable and shared libraries at runtime
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- Binary rewriting
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- Generate a new executable and/or library with instrumentation built-in
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- Statistical sampling
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- Periodic software interrupts per-thread
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- Process-level sampling
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- Background thread records process-, system- and device-level metrics while the application executes
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- Critical trace generation
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### Data Analysis
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- High-level summary profiles with mean/min/max/stddev statistics
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- Low overhead, memory efficient
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- Ideal for running at scale
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- Comprehensive traces
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- Every individual event/measurement
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- Critical trace analysis (alpha)
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### Parallelism API Support
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- HIP
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- HSA
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- Pthreads
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- MPI
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- Kokkos-Tools (KokkosP)
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- OpenMP-Tools (OMPT)
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### GPU Metrics
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- GPU hardware counters
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- HIP API tracing
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- HIP kernel tracing
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- HSA API tracing
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- HSA operation tracing
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- System-level sampling (via rocm-smi)
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- Memory usage
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- Power usage
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- Temperature
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- Utilization
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### CPU Metrics
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- CPU hardware counters sampling and profiles
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- CPU frequency sampling
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- Various timing metrics
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- Wall time
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- CPU time (process and/or thread)
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- CPU utilization (process and/or thread)
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- User CPU time
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- Kernel CPU time
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- Various memory metrics
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- High-water mark (sampling and profiles)
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- Memory page allocation
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- Virtual memory usage
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- Network statistics
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- I/O metrics
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- ... many more
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## Documentation
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The full documentation for [omnitrace](https://github.com/AMDResearch/omnitrace) is available at [amdresearch.github.io/omnitrace](https://amdresearch.github.io/omnitrace/).
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## Quick Start
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### Omnitrace Settings
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Generate an omnitrace configuration file using `omnitrace-avail -G omnitrace.cfg`. Optionally, use `omnitrace-avail -G omnitrace.cfg --all` for
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a verbose configuration file with descriptions, categories, etc. Modify the configuration file as desired, e.g. enable
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[perfetto](https://perfetto.dev/), [timemory](https://github.com/NERSC/timemory), sampling, and process-level sampling by default
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and tweak some sampling default values:
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```console
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# ...
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OMNITRACE_USE_PERFETTO = true
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OMNITRACE_USE_TIMEMORY = true
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OMNITRACE_USE_SAMPLING = true
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OMNITRACE_USE_PROCESS_SAMPLING = true
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# ...
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OMNITRACE_SAMPLING_FREQ = 50
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OMNITRACE_SAMPLING_CPUS = all
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OMNITRACE_SAMPLING_GPUS = $env:HIP_VISIBLE_DEVICES
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```
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Once the configuration file is adjusted to your preferences, either export the path to this file via `OMNITRACE_CONFIG_FILE=/path/to/omnitrace.cfg`
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or place this file in `${HOME}/.omnitrace.cfg` to ensure these values are always read as the default. If you wish to change any of these settings,
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you can override them via environment variables or by specifying an alternative `OMNITRACE_CONFIG_FILE`.
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### Omnitrace Executable
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The `omnitrace` executable is used to instrument an existing binary.
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```shell
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omnitrace --help
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omnitrace <omnitrace-options> -- <exe-or-library> <exe-options>
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```
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#### Binary Rewrite
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Rewrite the text section of an executable or library with instrumentation:
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```shell
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omnitrace -o app.inst -- /path/to/app
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```
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In binary rewrite mode, if you also want instrumentation in the linked libraries, you must also rewrite those libraries.
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Example of rewriting the functions starting with `"hip"` with instrumentation in the amdhip64 library:
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```shell
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mkdir -p ./lib
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omnitrace -R '^hip' -o ./lib/libamdhip64.so.4 -- /opt/rocm/lib/libamdhip64.so.4
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export LD_LIBRARY_PATH=${PWD}/lib:${LD_LIBRARY_PATH}
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```
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> ***Verify via `ldd` that your executable will load the instrumented library -- if you built your executable with***
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> ***an RPATH to the original library's directory, then prefixing `LD_LIBRARY_PATH` will have no effect.***
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Once you have rewritten your executable and/or libraries with instrumentation, you can just run the (instrumented) executable
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or exectuable which loads the instrumented libraries normally, e.g.:
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```shell
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./app.inst
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```
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If you want to re-define certain settings to new default in a binary rewrite, use the `--env` option. This `omnitrace` option
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will set the environment variable to the given value but will not override it. E.g. the default value of `OMNITRACE_PERFETTO_BUFFER_SIZE_KB`
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is 1024000 KB (1 GiB):
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```shell
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# buffer size defaults to 1024000
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omnitrace -o app.inst -- /path/to/app
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./app.inst
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```
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Passing `--env OMNITRACE_PERFETTO_BUFFER_SIZE_KB=5120000` will change the default value in `app.inst` to 5120000 KiB (5 GiB):
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```shell
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# defaults to 5 GiB buffer size
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omnitrace -o app.inst --env OMNITRACE_PERFETTO_BUFFER_SIZE_KB=5120000 -- /path/to/app
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./app.inst
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```
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```shell
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# override default 5 GiB buffer size to 200 MB
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export OMNITRACE_PERFETTO_BUFFER_SIZE_KB=200000
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./app.inst
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```
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#### Runtime Instrumentation
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Runtime instrumentation will not only instrument the text section of the executable but also the text sections of the
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linked libraries. Thus, it may be useful to exclude those libraries via the `-ME` (module exclude) regex option
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or exclude specific functions with the `-E` regex option.
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```shell
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omnitrace -- /path/to/app
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omnitrace -ME '^(libhsa-runtime64|libz\\.so)' -- /path/to/app
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omnitrace -E 'rocr::atomic|rocr::core|rocr::HSA' -- /path/to/app
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```
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### Visualizing Perfetto Results
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Visit [ui.perfetto.dev](https://ui.perfetto.dev) in your browser and open up the `.proto` file(s) created by omnitrace.
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## Using Perfetto tracing with System Backend
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Perfetto tracing with the system backend supports multiple processes writing to the same
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output file. Thus, it is a useful technique if Omnitrace is built with partial MPI support
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because all the perfetto output will be coalesced into a single file. The
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installation docs for perfetto can be found [here](https://perfetto.dev/docs/contributing/build-instructions).
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If you are building omnitrace from source, you can configure CMake with `OMNITRACE_INSTALL_PERFETTO_TOOLS=ON`
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and the `perfetto` and `traced` applications will be installed as part of the build process. However,
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it should be noted that to prevent this option from accidentally overwriting an existing perfetto install,
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all the perfetto executables installed by omnitrace are prefixed with `omnitrace-perfetto-`, except for the `perfetto`
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executable, which is just renamed `omnitrace-perfetto`.
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Enable `traced` and `perfetto` in the background:
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```shell
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pkill traced
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traced --background
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perfetto --out ./omnitrace-perfetto.proto --txt -c ${OMNITRACE_ROOT}/share/omnitrace.cfg --background
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```
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> ***NOTE: if the perfetto tools were installed by omnitrace, replace `traced` with `omnitrace-perfetto-traced` and***
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> ***`perfetto` with `omnitrace-perfetto`.***
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Configure omnitrace to use the perfetto system backend:
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```shell
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export OMNITRACE_PERFETTO_BACKEND=system
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```
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And finally, execute your instrumented application. Either the binary rewritten application:
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```shell
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omnitrace -o ./myapp.inst -- ./myapp
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./myapp.inst
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```
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Or with runtime instrumentation:
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```shell
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omnitrace -- ./myapp
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```
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