Go to file
Ruobing Han 9093f802b0
Delete LICENSE
remove the temporary license
2022-09-23 09:26:32 -04:00
.github/workflows update CI 2022-09-22 11:43:03 -04:00
common update HostTranslator with debug tools 2022-09-15 18:19:13 -04:00
compilation avoid unnecessary extend arrays 2022-09-23 09:15:10 -04:00
examples add static/dynamic shared memory example 2022-09-15 20:51:53 -04:00
external add external party for lock-free queue 2022-09-07 19:23:51 -04:00
runtime implement multistream APIs for CPU backend 2022-09-19 10:41:40 -04:00
.gitignore fix linting issues 2022-05-24 20:43:47 -04:00
.gitmodules add external party for lock-free queue 2022-09-07 19:23:51 -04:00
.pre-commit-config.yaml add CI 2022-01-13 13:30:45 -05:00
CMakeLists.txt update CMake to use official CUDA toolkit 2022-09-22 11:20:50 -04:00
CONTRIBUTING.md update how to contribute 2022-05-06 16:08:28 -04:00
README.md update README 2022-09-22 14:53:32 -04:00

README.md

CuPBoP: Cuda for Parallelized and Broad-range Processors

Introduction

CuPBoP is a framework which support executing unmodified CUDA source code on non-NVIDIA devices. Currently, CuPBoP support serveral CPU backends, including x86, AArch64, and RISC-V. Supporting Vortex (a RISC-V GPU) is working in progress.

Install

Prerequisites

Although CuPBoP does not require NVIDIA GPUs, it needs CUDA to compile the source programs to NVVM/LLVM IRs. CUDA toolkit can be built on machines without NVIDIA GPUs. For building CUDA toolkit, please refer to https://developer.nvidia.com/cuda-downloads.

Installation

  1. Clone from github

    git clone --recursive https://github.com/drcut/CuPBoP
    cd CuPBoP
    export CuPBoP_PATH=`pwd`
    export LD_LIBRARY_PATH=$CuPBoP_PATH/build/runtime:$CuPBoP_PATH/build/runtime/threadPool:$LD_LIBRARY_PATH
    export CUDA_PATH=/usr/local/cuda-11.7 # set to your own location
    
  2. Build CuPBoP

    mkdir build && cd build
    #set -DDEBUG=ON for debugging
    cmake .. \
       -DLLVM_CONFIG_PATH=`which llvm-config` \
       -DCUDA_PATH=$CUDA_PATH
    make
    

Run Vector Addition example

cd examples/vecadd
# Compile CUDA source code (both host and kernel) to bitcode files
clang++ -std=c++11 vecadd.cu \
      -I../.. --cuda-path=$CUDA_PATH \
      --cuda-gpu-arch=sm_50 -L$CUDA_PATH/lib64 \
      -lcudart_static -ldl -lrt -pthread -save-temps -v  || true
# Apply compilation transformations on the kernel bitcode file
$CuPBoP_PATH/build/compilation/kernelTranslator \
      vecadd-cuda-nvptx64-nvidia-cuda-sm_50.bc kernel.bc
# Apply compilation transformations on the host bitcode file
$CuPBoP_PATH/build/compilation/hostTranslator \
      vecadd-host-x86_64-unknown-linux-gnu.bc host.bc
# Generate object files
llc --relocation-model=pic --filetype=obj  kernel.bc
llc --relocation-model=pic --filetype=obj  host.bc
# Link with runtime libraries and generate the executable file
g++ -o vecadd -fPIC -no-pie \
      -I$CuPBoP_PATH/runtime/threadPool/include \
      -L$CuPBoP_PATH/build/runtime  \
      -L$CuPBoP_PATH/build/runtime/threadPool \
      host.o kernel.o \
      -I../.. -lc -lx86Runtime -lthreadPool -lpthread
# Execute
./vecadd

How to contribute?

Any kinds of contributions are welcome. Please refer to Contribution.md for more detail.

If you want to refer CuPBoP in your projects, please cite the related papers:

Contributors