Linux&Jetson Nano下编译安装ncnn

jupiter
2021-10-28 / 0 评论 / 816 阅读 / 正在检测是否收录...
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1.下载ncnn源码

项目地址:https://github.com/Tencent/ncnn
git clone https://github.com/Tencent/ncnn.git
cd ncnn
git submodule update --init

2.安装依赖

2.1 通用依赖

  • git
  • g++
  • cmake
  • protocol buffer (protobuf) headers files and protobuf compiler
  • glslang
  • opencv(用于编译案列)
sudo apt install build-essential git cmake libprotobuf-dev protobuf-compiler libvulkan-dev vulkan-utils libopencv-dev

2.2 vulkan header files and loader library (用于调用GPU,只用CPU的可以不用安装)

2.2.1 X86版本安装

# 为GPU安装Vulkan驱动
sudo apt install mesa-vulkan-drivers
# 安装vulkansdk
wget https://sdk.lunarg.com/sdk/download/1.2.189.0/linux/vulkansdk-linux-x86_64-1.2.189.0.tar.gz?Human=true -O vulkansdk-linux-x86_64-1.2.189.0.tar.gz
tar -xvf vulkansdk-linux-x86_64-1.2.189.0.tar.gz
export VULKAN_SDK=$(pwd)/1.2.189.0/x86_64

2.2.2 Jetson Nano安装

确认vulkan驱动是否安装正常
nvidia@xavier:/$ vulkaninfo
Xlib:  extension "NV-GLX" missing on display "localhost:10.0".
Xlib:  extension "NV-GLX" missing on display "localhost:10.0".
Xlib:  extension "NV-GLX" missing on display "localhost:10.0".
/build/vulkan-tools-WR7ZBj/vulkan-tools-1.1.126.0+dfsg1/vulkaninfo/vulkaninfo.h:399: failed with ERROR_INITIALIZATION_FAILED
  • 异常原因查找

image-20220616095801339

  • 通过vnc远程连接到图形界面后运行vulkaninfo
nano@nano:~$ vulkaninfo
===========
VULKAN INFO
===========
Vulkan Instance Version: 1.2.70

Instance Extensions:
====================
Instance Extensions    count = 16
    VK_KHR_device_group_creation        : extension revision  1
······
=========================
    minImageCount       = 2
    maxImageCount       = 8
    currentExtent:
        width       = 256
        height      = 256
    minImageExtent:
        width       = 256
        height      = 256
    maxImageExtent:
        width       = 256
        height      = 256
    maxImageArrayLayers = 1
······
安装vulkansdk
# 编译安装vulkansdk
sudo apt-get update && sudo apt-get install git build-essential libx11-xcb-dev libxkbcommon-dev libwayland-dev libxrandr-dev cmake
git clone https://github.com/KhronosGroup/Vulkan-Loader.git
cd Vulkan-Loader && mkdir build && cd build
../scripts/update_deps.py
cmake -DCMAKE_BUILD_TYPE=Release -DVULKAN_HEADERS_INSTALL_DIR=$(pwd)/Vulkan-Headers/build/install ..
make -j$(nproc)
export LD_LIBRARY_PATH=$(pwd)/loader
cd Vulkan-Headers
ln -s ../loader lib
export VULKAN_SDK=$(pwd)

3. 开始编译

  • CPU 版

    # 没安VULKAN运行这个
    cd ncnn
    mkdir -p build
    cd build
    cmake -DCMAKE_BUILD_TYPE=Release -DNCNN_VULKAN=OFF -DNCNN_SYSTEM_GLSLANG=ON -DNCNN_BUILD_EXAMPLES=ON ..
    make -j$(nproc)
  • GPU-X86

    # 有GPU安了VULKAN运行这个
    cd ncnn
    mkdir -p build
    cd build
    cmake -DCMAKE_BUILD_TYPE=Release -DNCNN_VULKAN=ON -DNCNN_SYSTEM_GLSLANG=ON -DNCNN_BUILD_EXAMPLES=ON ..
    make -j$(nproc)
  • GPU- Jetson Nano

    # Jetson Nano用这个
    cd ncnn
    mkdir -p build
    cd build
    cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/jetson.toolchain.cmake -DNCNN_VULKAN=ON -DCMAKE_BUILD_TYPE=Release -DNCNN_BUILD_EXAMPLES=ON ..
    make -j$(nproc)

    4.验证安装

    4.1 验证squeezenet

cd ../examples
../build/examples/squeezenet ../images/256-ncnn.png
nano@nano:/software/ncnn/examples$ ../build/examples/squeezenet ../images/256-ncnn.png
[0 NVIDIA Tegra X1 (nvgpu)]  queueC=0[16]  queueG=0[16]  queueT=0[16]
[0 NVIDIA Tegra X1 (nvgpu)]  bugsbn1=0  bugbilz=0  bugcopc=0  bugihfa=0
[0 NVIDIA Tegra X1 (nvgpu)]  fp16-p/s/a=1/1/1  int8-p/s/a=1/1/1
[0 NVIDIA Tegra X1 (nvgpu)]  subgroup=32  basic=1  vote=1  ballot=1  shuffle=1
532 = 0.168945
920 = 0.093323
716 = 0.063110
nvdc: start nvdcEventThread
nvdc: exit nvdcEventThread

4.1 验证benchncnn

cd ../benchmark
../build/benchmark/benchncnn 10 $(nproc) 0 0
nano@nano:/software/ncnn/benchmark$ ../build/benchmark/benchncnn 10 $(nproc) 0 0[0 NVIDIA Tegra X1 (nvgpu)]  queueC=0[16]  queueG=0[16]  queueT=0[16]
[0 NVIDIA Tegra X1 (nvgpu)]  bugsbn1=0  bugbilz=0  bugcopc=0  bugihfa=0
[0 NVIDIA Tegra X1 (nvgpu)]  fp16-p/s/a=1/1/1  int8-p/s/a=1/1/1
[0 NVIDIA Tegra X1 (nvgpu)]  subgroup=32  basic=1  vote=1  ballot=1  shuffle=1
loop_count = 10
num_threads = 4
powersave = 0
gpu_device = 0
cooling_down = 1
          squeezenet  min =   19.90  max =   22.82  avg =   20.82
     squeezenet_int8  min =   36.58  max =  236.35  avg =   66.89
           mobilenet  min =   24.75  max =   41.05  avg =   28.83
      mobilenet_int8  min =   42.95  max =   70.39  avg =   52.08
        mobilenet_v2  min =   31.84  max =   38.09  avg =   35.59
        mobilenet_v3  min =   29.77  max =   38.48  avg =   33.56
          shufflenet  min =   25.98  max =   36.90  avg =   30.86
       shufflenet_v2  min =   18.46  max =   27.65  avg =   20.49
             mnasnet  min =   22.63  max =   35.37  avg =   24.88
     proxylessnasnet  min =   27.85  max =   33.44  avg =   30.52
     efficientnet_b0  min =   34.85  max =   48.31  avg =   38.46
   efficientnetv2_b0  min =   56.62  max =   76.70  avg =   61.99
        regnety_400m  min =   28.31  max =   35.59  avg =   31.92
           blazeface  min =   14.40  max =   34.70  avg =   23.63
           googlenet  min =   55.01  max =   75.36  avg =   60.89
      googlenet_int8  min =  111.53  max =  315.94  avg =  167.58
            resnet18  min =   51.45  max =   77.21  avg =   59.26
       resnet18_int8  min =   81.99  max =  207.09  avg =  117.43
             alexnet  min =   69.98  max =  102.26  avg =   83.27
               vgg16  min =  302.14  max =  337.56  avg =  320.55
          vgg16_int8  min =  464.06  max =  601.92  avg =  540.28
            resnet50  min =  140.36  max =  176.66  avg =  159.53
       resnet50_int8  min =  299.16  max =  554.05  avg =  453.26
      squeezenet_ssd  min =   53.43  max =   78.75  avg =   63.67
 squeezenet_ssd_int8  min =   91.45  max =  215.14  avg =  123.13
       mobilenet_ssd  min =   66.30  max =   90.77  avg =   76.86
  mobilenet_ssd_int8  min =   89.05  max =  261.33  avg =  119.18
      mobilenet_yolo  min =  142.24  max =  182.72  avg =  154.48
  mobilenetv2_yolov3  min =   81.96  max =  107.17  avg =   91.93
         yolov4-tiny  min =  103.76  max =  138.15  avg =  115.43
           nanodet_m  min =   27.15  max =   36.88  avg =   32.00
    yolo-fastest-1.1  min =   33.21  max =   40.95  avg =   35.84
      yolo-fastestv2  min =   17.51  max =   29.54  avg =   21.32
  vision_transformer  min = 4981.82  max = 5576.98  avg = 5198.79
nvdc: start nvdcEventThread
nvdc: exit nvdcEventThread

参考资料

  1. how to build
  2. Vulkan Support on L4T
  3. NVIDIA vulkan driver的安装和Jetson平台上vulkan sdk的制作
  4. vulkaninfo failed with VK_ERROR_INITIALIZATION_FAILED
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