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Han Ruobing
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README.md
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README.md
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# COX: CUDA on X86
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# CuPBoP: Cuda for Parallelized and Broad-range Processors
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## Introduction
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This project consists of two parts: a series of LLVM passes that
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achieve a SPMD NVVM IR as input, and output the corresponding
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MPMD+SIMD version of LLVM IR which can be execute on CPU devices.
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CuPBoP is a framework which support executing unmodified CUDA source code
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on non-NVIDIA devices.
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Currently, CuPBoP support serveral CPU backends, including x86, AArch64, and RISC-V.
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## Install
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### Prerequisites
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* Linux: Verified on Ubuntu 18.04
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* LLVM10.0
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* NVIDIA CUDA-toolkit
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* x86 CPU
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* pthread
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* GCC 7.5.0
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- Linux: Verified on Ubuntu 18.04
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- LLVM10.0
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- NVIDIA CUDA-toolkit
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- x86 CPU
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- pthread
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- GCC 7.5.0
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### Installation
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1. Clone from github
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```bash
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git clone https://github.com/drcut/open_source_template
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cd open_source_template
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```
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```bash
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git clone https://github.com/cupbop/CuPBoP
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cd CuPBoP
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export CuPBoP_PATH=`pwd`
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export LD_LIBRARY_PATH=$CuPBoP_PATH/build/runtime:$CuPBoP_PATH/build/runtime/threadPool:$LD_LIBRARY_PATH
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```
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2. Build the transformer for NVVM IR to LLVM IR for X86
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2. As CuPBoP relies on CUDA structures, we need to download the CUDA header file
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```bash
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mkdir build && cd build
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cmake .. -DLLVM_CONFIG_PATH=`which llvm-config` # need path to llvm-config
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make
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```
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```bash
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wget https://www.dropbox.com/s/r18io0zu3idke5p/cuda-header.tar.gz?dl=1
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tar -xzf 'cuda-header.tar.gz?dl=1'
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cp -r include/* runtime/threadPool/include/
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```
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## Run Vecadd samples
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3. Other CUDA files are also required for compiling CUDA source code to LLVM IR
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```bash
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wget https://www.dropbox.com/s/4pckqsjnl920gpn/cuda-10.1.tar.gz?dl=1
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tar -xzf 'cuda-10.1.tar.gz?dl=1'
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```
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4. Build CuPBoP
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```bash
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mkdir build && cd build
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cmake .. -DLLVM_CONFIG_PATH=`which llvm-config` # need path to llvm-config
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make
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```
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## Run HIST application in Hetero-mark benchmark
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```bash
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# Generate bitcode from human-readable LLVM IR
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llvm-as ../compilation/examples/vecadd/kernel-cuda-nvptx64-nvidia-cuda-sm_61.ll
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# use LLVM passes to transform NVVM IR (SPMD) to LLVM IR (MPMD+SIMD).
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# NOTE: we hard-code the grid size (1, 1, 1)
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# and block size (1024, 1, 1) into the generated LLVM IR
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./compilation/nvvm2x86 \
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../compilation/examples/vecadd/kernel-cuda-nvptx64-nvidia-cuda-sm_61.bc \
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kernel.bc 1 1 1 32 1 1
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# generate object file from LLVM IR
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llc --filetype=obj kernel.bc
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# link generated kernel function
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# with host function and generate excutable file
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g++ ../compilation/examples/vecadd/host.cpp \
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kernel.o -lpthread -o vecadd_example
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# execute the executable file
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./vecadd_example
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# Clone Hetero-mark benchmark
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git clone https://github.com/drcut/SC_evaluate
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cd SC_evaluate/Hetero-cox/src/hist
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# Compile CUDA source code to LLVM IR
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# this may raise error due to absence of CUDA library, just ignore them
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clang++ -std=c++11 cuda/hist_cuda_benchmark.cu \\
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-I../.. --cuda-path=$CuPBoP_PATH/cuda-10.1 \\
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--cuda-gpu-arch=sm_50 -L$CuPBoP_PATH/cuda-10.1/lib64 \\
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-lcudart_static -ldl -lrt -pthread -save-temps -v || true
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# Translate host/kernel LLVM IR to formats that suitable for CPU
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$CuPBoP_PATH/build/compilation/kernelTranslator hist_cuda_benchmark-cuda-nvptx64-nvidia-cuda-sm_50.bc kernel.bc
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$CuPBoP_PATH/build/compilation/hostTranslator hist_cuda_benchmark-host-x86_64-unknown-linux-gnu.bc host.bc
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# generate object files
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llc --relocation-model=pic --filetype=obj kernel.bc
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llc --relocation-model=pic --filetype=obj host.bc
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# generate CPU executable file
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g++ -o hist -fPIC -no-pie \\
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-I$CuPBoP_PATH/runtime/threadPool/include \\
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-L$CuPBoP_PATH/build/runtime \\
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-L$CuPBoP_PATH/build/runtime/threadPool \\
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cuda/main.cc host.o kernel.o *.cc ../common/benchmark/*.cc \\
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../common/command_line_option/*.cc ../common/time_measurement/*.cc \\
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-I../.. -lpthread -lc -lx86Runtime -lthreadPool
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# execute and verify
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./hist -q -v
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```
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## Author
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[Ruobing Han](https://drcut.github.io/) is a CS phd student in
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Georgia Institute Technology, under the supervision
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of Prof. [Hyesoon Kim](https://www.cc.gatech.edu/~hyesoon/).
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