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README
Apache-2.0

RISCV-AI-2024

仓库结构

  • Configs:profile以及nginx配置

  • Docs:包括作品申报书,PPT以及测试结果等材料

    • Finale:决赛资料
    • Preliminary:初赛资料
  • rv64ai-frontend:项目前端代码

    • src:核心代码
    • dist:部署路径
  • rv64ai-backend:项目后端代码

    • main.py:启动脚本
  • rv64ai-faas:OpenFaaS部署函数

  • rv64ai-opencl:OpenCL算子优化测试

  • python-dependencies:本项目中用到的python依赖库

  • README.md

  • .gitignore

  • 决赛PPT.pptx

  • 决赛演示视频.mp4

部署过程

# 配置环境变量并进入Python虚拟环境
# profile文件在Configs/etc/路径下
source /etc/profile
# 启动后端服务
cd rv64ai-backend
# 确认下载好所有依赖
python3 main.py
# 启动nginx
# nginx配置文件在Configs/etc/nginx中
nginx -t
nginx -s reload

启动后即可在本地访问项目:http://127.0.0.1

接入网络后,在同一局域网下的设备均可通过开发板ip地址访问本项目

项目截图

  • 若需要重新部署项目,请参考以下步骤在算能云空间或其他环境中进行

项目部署

Pytorch

reference①:https://docs.qq.com/doc/DRURYclJlenBVVElZ

reference②:https://blog.csdn.net/m0_49267873/article/details/135670989

# 克隆pytorch仓库
https://github.com/pytorch/pytorch.git
# 下载算能cpuinfo
# 其他硬件环境中可以不执行这一步
cd pytorch/third_party
rm -r cpuinfo
git clone https://github.com/sophgo/cpuinfo.git
cd ..
  • 修改代码文件
# 1.aten/src/ATen/CMakeLists.txt
# 将语句
if(NOT MSVC AND NOT EMSCRIPTEN AND NOT INTERN_BUILD_MOBILE)
# 替换为
if(FALSE)
# ---
# 2.caffe2/CMakeLists.txt
# 将语句
target_link_libraries(${test_name}_${CPU_CAPABILITY} c10 sleef gtest_main)
# 替换为
target_link_libraries(${test_name}_${CPU_CAPABILITY} c10 gtest_main)
# 3.test/cpp/api/CMakeLists.txt
# 在语句
add_executable(test_api ${TORCH_API_TEST_SOURCES})
# 后添加
target_compile_options(test_api PUBLIC -Wno-nonnull)
  • 编译工具链安装
apt install libblas-dev m4 cmake cython3 ccache
  • 编译OpenBLAS
# 克隆源码仓库
git clone https://github.com/xianyi/OpenBLAS.git
cd OpenBLAS
make -j4
# 开始编译安装
make PREFIX=/usr/local/OpenBLAS install
# 添加环境变量
vim /etc/profile
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/OpenBLAS/lib/
export OMP_NUM_THREADS=1
# 使变量生效
source /etc/profile
  • python环境配置
apt install python3
apt install python-is-python3 python-dev-is-python3
apt autoremove
apt install python3-pip
pip install pyyaml
python3 -m pip install numpy --upgrade -i https://pypi.tuna.tsinghua.edu.cn/simple
  • 添加pytorch环境变量
vim /etc/profile
export USE_CUDA=0 #不编译CUDA版本
export USE_DISTRIBUTED=0 #不支持分布式
export USE_MKLDNN=0 #不支持MKLDNN
export MAX_J0BS=2 #最大线程数 ,按需填写
source /etc/profile
  • 开始编译
python3 setup.py install --cmake
# 若编译过程中遇到undefined reference to `__atomic_exchange_1'问题
# 则退出编译过程,执行以下命令
# path为存放libtorch_cpu.so的路径
patchelf --add-needed libatomic.so.1 /path/libtorch_cpu.so
# 重新编译
python3 setup.py install --cmake

Paddle

reference:https://blog.csdn.net/skywalk8163/article/details/136264198

# 克隆paddle源码
git clone https://github.com/paddlepaddle/paddle
# 下载依赖
pip3 install protobuf
# 进入paddle目录
cd paddle

参考https://github.com/PaddlePaddle/Paddle/commit/d3db3835ec14dc5ca8d4c8a769164103f4703c64修改paddle源码,或直接用本仓库中paddle目录下的文件替换即可

# 开始编译
mkdir build
cd build
cmake ../ -DWITH_GPU=OFF -DWITH_RISCV=ON
make -j4 TARGET=RISCV64_GENERIC
# 编译完成后进行安装
cd python/dist
ls # 查看是否存在编译好的whl文件: paddlepaddle-0.0.0-cp38-cp38-linux_riscv64.whl
pip3 install paddlepaddle-0.0.0-cp38-cp38-linux_riscv64.whl

Python依赖

安装python-dependencies中的python依赖库

部份依赖可在https://launchpad.net/ubuntu/+search获取

Front end

cd rv64ai-front
# 待部署的文件在dist目录中
# 也可以用yarn通过源码重新构建生成
yarn build

Back end

  • 添加环境变量
vim ~/.bashrc
export HF_ENDPOINT=https://hf-mirror.com
source ~/.bashrc
  • 启动后端项目
cd rv64ai-backend
python3 main.py

Nginx

# 安装nginx
apt install nginx
# 启动nginx
nginx
# 修改nginx配置文件
vim /etc/nginx/sites-available/default
  • 修改default文件中的server字段,如下所示
server { 
        listen 80 default_server; 
        listen [::]:80 default_server; 
 
        root /tmp/rv64ai-front/dist; 
        index index.html index.htm index.nginx-debian.html; 
        server_name _;
    
		location / { 
                # First attempt to serve request as file, then 
                # as directory, then fall back to displaying a 404. 
                try_files $uri $uri/ =404; 
        } 
 
        location /api/ { 
                proxy_pass  http://127.0.0.1:5000; 
                proxy_set_header Host $proxy_host; 
                proxy_set_header X-Real-IP $remote_addr; 
                proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; 
                proxy_read_timeout 1000; 
        } 
 
        location /static/ {  
                proxy_pass  http://127.0.0.1:5000;  
                proxy_set_header Host $proxy_host;  
                proxy_set_header X-Real-IP $remote_addr;  
                proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; 
        } 
}
  • 验证并重新加载nginx配置文件
nginx -t
nginx -s reload

成功后即可使用ip地址或域名访问到项目

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