mperf

mperf is a modular micro-benchmark/toolkit for kernel performance analysis.

Features.

Investigate the basic micro-architectural parameters(uarch) of the target CPU/GPU.
Draw graph of hierarchical roofline model, used to evaluate performance.
Collect CPU/GPU PMU events data.
Analyze CPU/GPU PMU events data(TMA Methodology and customized metrics), used to identify performance bottlenecks.
OpenCL Linter, used to guide manual OpenCL kernel optimization[TBD].
C++ Project
support platform: ARM CPUs, Mali GPUs, Adreno 6xx GPUs
Lightweight and embeddable library
The iOS platform is not yet fully functional.

Installation

mperf support CMake build system and require CMake version upper than 3.15.2, you can compile the mperf follow the step:

clone or download the project

git clone https://github.com/MegEngine/mperf.git
git submodule update --init --recursive

choose a test platform
- if you will test arm processor in android OS
  - a ndk is required
    - download the NDK and extract to the host machine
    - set the NDK_ROOT env to the path of extracted NDK directory
- if you will test x86 processor in linux OS
  - a gcc or clang compiler should find by cmake through PATH env

if your target test OS is android，run the android_build.sh to build it

print the usage about android_build.sh
```
./android_build.sh -h
```
build for armv7 cpu
```
./android_build.sh -m armeabi-v7a
```

build for arm64 cpu

./android_build.sh [-m arm64-v8a] // default march is arm64-v8a

build with mali mobile gpu

./android_build.sh -g mali [arm64-v8a, armeabi-v7a]

build with adreno mobile gpu

./android_build.sh -g adreno [arm64-v8a, armeabi-v7a]

build with pfm

./android_build.sh -p [arm64-v8a, armeabi-v7a]

build in debug mode

./android_build.sh -d [arm64-v8a, armeabi-v7a]

build with your custom install directory

./android_build.sh -i /your/custom/cmake/install/prefix [arm64-v8a, armeabi-v7a]
e.g.: ./android_build.sh -i ~/mperf_install [-m arm64-v8a] // default march is arm64-v8a

if you target test OS is linux，if you want to enable pfm add -DMPERF_ENABLE_PFM=ON to cmake command
```
cmake -S . -B "build-x86" -DMPERF_ENABLE_PFM=ON
cmake --build "build-x86" --config Release 
```
after build, some executable files are stored in mperf build_dir/apps directory. And you can install the mperf to your system path or your custom install directory by
```
cmake --build <mperf_build_dir> --target install 
e.g.: cmake --build ./build-arm64-v8a/ --target install
```

and now, you can use find_package command to import the installed mperf, and use like

set(mperf_DIR /path/to/your/installed/mperfConfig.cmake) # Note, it's the dirname of mperfConfig.cmake, e.g. set(mperf_DIR ~/mperf_install/lib/cmake/mperf/)
find_package(mperf REQUIRED)
target_link_libraries(your_target mperf::mperf)

alternatively, add_subdirectory(mperf) will incorporate the library directly in to your's CMake project.

Usage

basic usage for mperf xpmu module:

mperf::CpuCounterSet cpuset = "CYCLES,INSTRUCTIONS,...";
mperf::XPMU xpmu(cpuset);
xpmu.run();

... // add your function to be measured

xpmu.sample();
xpmu.stop();

please see cpu_pmu / mali_pmu / adreno_pmu for more details.

basic usage for mperf tma module:

mperf::tma::MPFTMA mpf_tma(mperf::MPFXPUType::A55);
mpf_tma.init(
        {"Frontend_Bound", "Bad_Speculation", "Backend_Bound", "Retiring", ...});
size_t gn = mpf_tma.group_num();
for (size_t i = 0; i < gn; ++i) {
    mpf_tma.start(i);
    for (size_t j = 0; j < iter_num; ++j) {
        ... // add your function to be measured
    }
    mpf_tma.sample_and_stop(iter_num);
}
mpf_tma.deinit();

please see arm_cpu_tma for more details.

Source Directory Structure

apps Various user examples, please see apps doc for more details.
eca A module for collecting and analyzing PMU events data(Including TMA analysis).
uarch A set of low-level micro-benchmarks to investigate the basic micro-architectural parameters(uarch) of the target CPU/GPU.
doc Some documents about roofline and tma usage, please see index for the list.
cmake Some cmake relative files.
common Some common helper functions.
third_party Some dependent libraries.
linter OpenCL Linter [TBD].

Tutorial

A tutorial about how to optimize matmul to achieve peak performance on ARM A55 core, which will illustrate the basic logic of how to use mperf help your optimization job, please reference optimize the matmul with the help of mperf.

License

mperf is licensed under the Apache-2.0 license.

zpeng11 / mperf