OpenCNN

A winograd’s minimal filtering algorithm implementation in CUDA

Requirements

• CUDA Toolkit
• cuDNN
• CMake

Build the project

git clone https://github.com/UDC-GAC/openCNN.git
cd openCNN

GPU architecture code must be specified inside the Makefile before compiling.

make

Compile time macros have been defined for testing purposes. They can be specified in the MakeFile according to the following values:

$OUT (builds an specific output storage and transform version):
  - BASE: baseline layout
  - OPTSTS64 (default): optSTS64 layout
  - OUTSTS64_CMP: optSTS64_compact layout
  - OUTLDS64: optLDS64 layout

Run examples

(Recommended before time measurement) Lock the clocks:

sudo nvidia-smi -i 0 -pm 1
sudo nvidia-smi -lgc 1750 -i 0

1. OpenCNN benchmark

cd bench
./bench.sh

2. Instruction-level microbenchmarking (Require Turing devices). TuringAs (https://github.com/daadaada/turingas) must be installed for running instruction-level microbenchmarking.

cd bench/smem/STS
make
./test

Citation

If you find this tool helpful, please cite:

@Article{math9172033,
AUTHOR = {Castro, Roberto L. and Andrade, Diego and  Fraguela, Basilio B.},
TITLE = {OpenCNN: A Winograd Minimal Filtering Algorithm Implementation in CUDA},
JOURNAL = {Mathematics},
VOLUME = {9},
YEAR = {2021},
NUMBER = {17},
ARTICLE-NUMBER = {2033},
URL = {https://www.mdpi.com/2227-7390/9/17/2033},
ISSN = {2227-7390},
DOI = {10.3390/math9172033}
}

License

Apache-2.0 License

-- Roberto López Castro