Updated features docs (#98)

This commit is contained in:
Jonathan R. Madsen
2022-07-21 12:56:10 -05:00
committed by GitHub
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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.***
## Overview
AMD Research is seeking to improve observability and performance analysis for software running on AMD heterogeneous systems.
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/),
you will find many of the capabilities of these tools available via Omnitrace in addition to many new capabilities.
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.
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.
Omnitrace supports interactive visualization of comprehensive traces in the web browser in addition to high-level summary profiles with mean/min/max/stddev statistics.
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
such as the memory usage, page-faults, and context-switches, and thread-level metrics such as memory usage, CPU time, and numerous hardware counters.
### Data Collection Modes
- Dynamic instrumentation
- Runtime instrumentation
- Instrument executable and shared libraries at runtime
- Binary rewriting
- Generate a new executable and/or library with instrumentation built-in
- Statistical sampling
- Periodic software interrupts per-thread
- Process-level sampling
- Background thread records process-, system- and device-level metrics while the application executes
- Critical trace generation
### Data Analysis
- High-level summary profiles with mean/min/max/stddev statistics
- Low overhead, memory efficient
- Ideal for running at scale
- Comprehensive traces
- Every individual event/measurement
- Critical trace analysis (alpha)
### Parallelism API Support
- HIP
- HSA
- Pthreads
- MPI
- Kokkos-Tools (KokkosP)
- OpenMP-Tools (OMPT)
### GPU Metrics
- GPU hardware counters
- HIP API tracing
- HIP kernel tracing
- HSA API tracing
- HSA operation tracing
- System-level sampling (via rocm-smi)
- Memory usage
- Power usage
- Temperature
- Utilization
### CPU Metrics
- CPU hardware counters sampling and profiles
- CPU frequency sampling
- Various timing metrics
- Wall time
- CPU time (process and/or thread)
- CPU utilization (process and/or thread)
- User CPU time
- Kernel CPU time
- Various memory metrics
- High-water mark (sampling and profiles)
- Memory page allocation
- Virtual memory usage
- Network statistics
- I/O metrics
- ... many more
## Documentation
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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- Generate a new executable and/or library with instrumentation built-in
- Statistical sampling
- Periodic software interrupts per-thread
- Background thread sampling
- Record process and system-level values while an application executes
- Process-level sampling
- Background thread records process-, system- and device-level metrics while the application executes
- Critical trace generation
### Data Analysis
- Critical trace generation (beta)
- Support for
- High-level summary profiles with mean/min/max/stddev statistics
- Low overhead, memory efficient
- Ideal for running at scale
- Comprehensive traces
- Every individual event/measurement
- Critical trace analysis (alpha)
### Parallelism API Support
- Built-in MPI support
- Kokkos-Tools support
- HIP
- HSA
- Pthreads
- MPI
- Kokkos-Tools (KokkosP)
- OpenMP-Tools (OMPT)
### GPU Metrics
- GPU hardware counters
- HIP API tracing
- ROCM HSA API tracing
- Kernel runtime tracing
- HIP kernel tracing
- HSA API tracing
- HSA operation tracing
- System-level sampling (via rocm-smi)
- Memory usage
- Power usage