配置gem5-gpu模拟环境

// 系统：ubuntu 14.04,显卡：支持CUDA的显卡。建议换aliyun的源！先clean软件源再update。
// 在Ubuntu 16.04上试过，配好环境变量，编译出错（把14.04上编译好的cuda和sdk复制过去也不行），把编译好的gem5-gpu复制到16.04也不行（运行时缺少libprotobuf.so.8,16.04安装的so.9）
sudo apt-get update

// 之所以采用apt-get安装驱动，是因为用下载好的驱动二进制文件安装，提示关于 X 服务的问题。因为显卡比较老，所以安装了legacy drive。
sudo apt-get install nvidia-304 // 340 375也可以，可以去Ubuntu官网查看12.04 14.04 16.04所有的软件包及其依赖
sudo apt-get install nvidia--dev
// 下面两个好像已经安装好
sudo apt-get install nvidia-settings
sudo apt-get install nvidia-current
// 安装开发环境，opencl，cuda
sudo apt-get install nvidia-current-dev
sudo add-apt-repository ppa:xorg-edgers/ppa
sudo apt-get update
// 一些依赖，编译SDK用！
sudo apt-get install libxext-dev libxi-dev x11proto-xext-dev libice-dev libsm-dev libxt-dev libxmu-headers libxmu-dev freeglut3-dev libcr-dev libX11-dev libglu1-mesa
// Install all of gem5's dependencies
sudo apt-get update -y
sudo apt-get install -y \
        build-essential \
        python-dev \
        scons \
        swig \
        zlib1g-dev \
        m4 \
        libprotobuf-dev \
        python-protobuf \
        protobuf-compiler \
        libgoogle-perftools-dev
// 安装水银分布式版本管理
sudo apt-get install --no-install-recommends -y mercurial
// 主目录下新建水银配置文件 .hgrc,内容如下：
[ui]
username=yourName<yourEmail@Address.com>
[extensions]
mq=
# Install dependencies for gem5-gpu (CUDA benchmarks)
sudo apt-get install -y \
            gcc-4.6 \
            g++-4.6 \
            python \
            wget \
    gcc-4.4 \
    g++-4.4 \
    gcc-4.8 \
    g++-4.8
# if your system is ubuntu 12.04, to install gcc-4.8 is difficult， if your system is 14.04, skip following
//REF: http://blog.csdn.net/dezhihuang/article/details/53432465
//REF: http://highlightz.blog.163.com/blog/static/23801000420141115103727888
#sudo add-apt-repository ppa:ubuntu-sdk-team/ppa
#sudo add-apt-repository ppa:ubuntu-toolchain-r/test
#setup gcc & g++,4.4  4.6  4.8 都要设置！
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.4
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.4 40
# setup default c compiler
sudo update-alternatives --config g++
sudo update-alternatives --config gcc
# Obtaining CUDA Toolkit and CUDA SDK,目前该模拟器只支持 CUDA3.2！
wget http://developer.download.nvidia.com/compute/cuda/3_2_prod/toolkit/cudatoolkit_3.2.16_linux_64_ubuntu10.04.run
wget http://developer.download.nvidia.com/compute/cuda/3_2_prod/sdk/gpucomputingsdk_3.2.16_linux.run
# Note: need to make sure return is pressed
sudo bash cudatoolkit_3..16_linux_64_ubuntu10..run
# Note: 如果toolkit是默认路径,就不需手动输入toolkit路径，直接回车，如果要将SDK安装到非用户主目录下，需要root权限！
bash gpucomputingsdk_3..16_linux.run
# edit ~/.bashrc，需保证路径值与toolkit、sdk的安装路径一致，编辑后需要重新开启一个终端，使环境变量被读取！
export CUDAHOME=/usr/local/cuda;
export PATH=$PATH:/usr/local/cuda/bin;
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/lib;
export LIBRARY_PATH=$LIBRARY_PATH:/home/chen/NVIDIA_GPU_Computing_SDK/C/lib;
export NVIDIA_CUDA_SDK_LOCATION=/home/chen/NVIDIA_GPU_Computing_SDK;

// shift to gcc-4.4 & g++-4.4
# WORKDIR /home/chen/NVIDIA_GPU_Computing_SDK/C/common
make
# WORKDIR /home/chen/NVIDIA_GPU_Computing_SDK/C
make

# 安装 python-pydot，用于生成拓扑结构
sudo apt-get install python-pydot
# 新建文件夹“gem5-gpu”作为GEM5-GPU-HOME，这个文件夹可以是其他名字
# WORKDIR GEM5-GPU-HOME
# Clone gem5 and gem5-patches
hg qclone http://repo.gem5.org/gem5 -p http://gem5-gpu.cs.wisc.edu/repo/gem5-patches
cd gem5/
hg update -r  # 执行完这条命令后，终端提示文件变动情况： N files updated,  files merged, M files removed,  files unresolved
hg qpush -a
cd ../
# Clone GPGPU-Sim and GPGPU-Sim patches ( separate options)
hg qclone http://gem5-gpu.cs.wisc.edu/repo/gpgpu-sim -p http://gem5-gpu.cs.wisc.edu/repo/gpgpu-sim-patches
cd gpgpu-sim
hg qpush -a
cd ../
# Clone gem5-gpu glue code
hg clone http://gem5-gpu.cs.wisc.edu/repo/gem5-gpu

# 现在目录结构为:
# gem5-gpu // 这是GEM5-GPU-HOME
#     -gem5-gpu
#     -gem5
#     -gpgpu-sim

# Build, gcc-4.8 & g++-4.8 are used
cd gem5
scons -j 3 build/X86_VI_hammer_GPU/gem5.opt --default=X86 EXTRAS=../gem5-gpu/src:../gpgpu-sim/ PROTOCOL=VI_hammer GPGPU_SIM=True

# Obtaining Benchmarks，make sure benchmarks' dir be located in GEM5-GPU-HOME!
# WORKDIR GEM5-GPU-HOME
hg clone https://gem5-gpu.cs.wisc.edu/repo/benchmarks/

# 现在目录结构为:
# gem5-gpu // GEM5-GPU-HOME
#     -gem5-gpu
#     -gem5
#     -gpgpu-sim
#     -benchmarks

# Compile libcuda,gcc-4.4 & g++-4.4 are used，libcuda是benchmarks的依赖，不可跳过libcuda直接编译benchmark！
[gem5-gpu/benchmarks] cd libcuda
[gem5-gpu/benchmarks/libcuda] make
# Example of Compiling a Benchmark，指定 makefile 为 gem5-fusion！
[gem5-gpu/benchmarks] cd rodinia/backprop
[gem5-gpu/benchmarks/rodinia/backprop] make gem5-fusion
# Example of Running a Benchmark
build/X86_VI_hammer_GPU/gem5.opt ../gem5-gpu/configs/se_fusion.py -c ../benchmarks/rodinia/backprop/gem5_fusion_backprop -o 16
// 注意：在ubuntu 14.04上使用相对路径可能会出现 fatal: syscall gettid (#186) unimplemented.将命令中的相对路径改为绝对路径.
// 编译 benchmark 脚本样例：

#!/bin/bash
 
extra=""
if [ ! -z "$1" ]
then
    extra="$1"
fi
 
for i in BFS BS CEDD CEDT HSTI HSTO PAD RSCD RSCT SC SSSP TQ TQH TRNS
do
    cd $i
    make $extra
    make clean
    cd ..
done
cd ..