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https://github.com/UniHD-CEG/cuda-flux
CUDA Flux is a profiler for GPU applications which reports the basic block executions frequencies of compute kernels
https://github.com/UniHD-CEG/cuda-flux
Last synced: about 1 month ago
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CUDA Flux is a profiler for GPU applications which reports the basic block executions frequencies of compute kernels
- Host: GitHub
- URL: https://github.com/UniHD-CEG/cuda-flux
- Owner: UniHD-CEG
- License: mit
- Created: 2019-11-14T10:07:54.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2021-03-15T07:20:22.000Z (over 3 years ago)
- Last Synced: 2024-08-02T18:40:58.664Z (4 months ago)
- Language: C++
- Size: 586 KB
- Stars: 29
- Watchers: 3
- Forks: 6
- Open Issues: 4
-
Metadata Files:
- Readme: Readme.md
- License: LICENSE.TXT
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README
# CUDA Flux: A Lightweight Instruction Profiler for CUDA Applications
CUDA Flux is a profiler for GPU applications which reports the basic block executions frequencies of compute kernels
# Dependencies
* LLVM:
CUDA Flux is tested and developed with llvm 11.0
```
git clone --branch release/11.x https://github.com/llvm/llvm-project.git
```
CMake config:
```
cmake -DLLVM_ENABLE_PROJECTS=clang -DCMAKE_INSTALL_PREFIX=/opt/llvm-11.0 \
-DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_ENABLE_DOXYGEN=OFF -DLLVM_BUILD_DOCS=OFF -GNinja \
-DLLVM_INSTALL_BINUTILS_SYMLINKS=ON -DBUILD_SHARED_LIBS=ON \
../llvm
```
* re2c lexer generator - http://re2c.org/ (make sure to check your package manager first)
* CUDA SDK >= 9.0
* Python (python3 preferred) with the yaml package installed
* environment-modules (optional, but recommended)
## Install
```
# Make sure LLVM and CUDA are in your paths
git clone https://github.com/UniHD-CEG/cuda-flux.git
cd cuda-flux && mkdir build && cd build
cmake -DCMAKE_INSTALL_PREFIX=/opt/cuda-flux .. # change install dir if you wish
make install
```
## Usage
Make sure the bin folder of your cuda-flux installation is in your path.
Better: use environment-module to load cuda-flux.
```
module load /opt/cuda-flux/module/cuda_flux # LLVM and CUDA need to be loaded first!
```
Compile your CUDA application:
```
clang_cf++ --cuda-gpu-arch=sm_35 -std=c++11 -lcudart test/saxpy.cu -o saxpy`
```
Execute the binary like usual: `./saxpy`
Output:
If any kernel was executed there is a bbc.txt file. Each kernel execution
results in a line with the following information:
* kernel name
* gridDim{X,Y,Z}
* blockDim{X,Y,Z}
* shared Memory size
* Profiling Mode (full, CTA, warp)
* List of executions counters for each block
The PTX instructions for all kernels are stored in the `PTX_Analysis.yml`
file. The order of the Basic Blocks corresponds with the order of the
counters in the bbc.txt file.
Profiling mode is controlled by the environment variable `MEKONG_PROFILINGMODE`. If is is not set or set to 0 all threads are profiled, which is the recommended setting. `export MEKONG_PROFILINGMODE=1` will only profile one CTA and `export MEKONG_PROFILINGMODE=2` will profile only one warp.