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wiki-sync-bot edited this page Dec 4, 2024 · 1 revision

Git clone ncnn repo with submodule

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

Build for Linux

Install required build dependencies:

  • git
  • g++
  • cmake
  • protocol buffer (protobuf) headers files and protobuf compiler
  • glslang
  • (optional) LLVM OpenMP header files # If building with Clang, and multithreaded CPU inference is desired
  • (optional) vulkan header files and loader library # If building with Vulkan, without simplevk
  • (optional) opencv # For building examples

Generally if you have Intel, AMD or Nvidia GPU from last 10 years, Vulkan can be easily used.

On some systems there are no Vulkan drivers easily available at the moment (October 2020), so you might need to disable use of Vulkan on them. This applies to Raspberry Pi 3 (but there is experimental open source Vulkan driver in the works, which is not ready yet). Nvidia Tegra series devices (like Nvidia Jetson) should support Vulkan. Ensure you have most recent software installed for best experience.

On Debian 10+, Ubuntu 20.04+, or Raspberry Pi OS, you can install all required dependencies using:

sudo apt install build-essential git cmake libprotobuf-dev protobuf-compiler libomp-dev libvulkan-dev vulkan-tools libopencv-dev

On earlier Debian or Ubuntu, you can install all required dependencies using:

sudo apt install build-essential git cmake libprotobuf-dev protobuf-compiler libomp-dev libvulkan-dev vulkan-utils libopencv-dev

On Redhat or Centos, you can install all required dependencies using:

sudo yum install build-essential git cmake libprotobuf-dev protobuf-compiler libvulkan-dev vulkan-utils libopencv-dev

To use Vulkan backend install Vulkan header files, a vulkan driver loader, GLSL to SPIR-V compiler and vulkaninfo tool. Preferably from your distribution repositories. Alternatively download and install full Vulkan SDK (about 200MB in size; it contains all header files, documentation and prebuilt loader, as well some extra tools and source code of everything) from https://vulkan.lunarg.com/sdk/home

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 -xf vulkansdk-linux-x86_64-1.2.189.0.tar.gz
export VULKAN_SDK=$(pwd)/1.2.189.0/x86_64

To use Vulkan after building ncnn later, you will also need to have Vulkan driver for your GPU. For AMD and Intel GPUs these can be found in Mesa graphics driver, which usually is installed by default on all distros (i.e. sudo apt install mesa-vulkan-drivers on Debian/Ubuntu). For Nvidia GPUs the proprietary Nvidia driver must be downloaded and installed (some distros will allow easier installation in some way). After installing Vulkan driver, confirm Vulkan libraries and driver are working, by using vulkaninfo or vulkaninfo | grep deviceType, it should list GPU device type. If there are more than one GPU installed (including the case of integrated GPU and discrete GPU, commonly found in laptops), you might need to note the order of devices to use later on.

Nvidia Jetson

The Vulkan driver is a default component of the Linux For Tegra BSP release, check the device list.

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

Raspberry Pi

Vulkan drivers do exists, but are not mature. You are free to experiment at your own discretion, and report results and performance.

cd ncnn
mkdir -p build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DNCNN_VULKAN=ON -DNCNN_BUILD_EXAMPLES=ON ..
make -j$(nproc)

You can add -GNinja to cmake above to use Ninja build system (invoke build using ninja or cmake --build .).

For Raspberry Pi 3 on 32bit OS, add -DCMAKE_TOOLCHAIN_FILE=../toolchains/pi3.toolchain.cmake to cmake. You can also consider disabling Vulkan support as the Vulkan drivers for Raspberry Pi are still not mature, but it doesn't hurt to build the support in, but not use it.

POWER

For POWER9 with Clang:

cd ncnn
mkdir -p build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=../toolchains/power9le-linux-gnu-vsx.clang.toolchain.cmake -DNCNN_VULKAN=ON -DNCNN_BUILD_EXAMPLES=ON ..
make -j$(nproc)

To use GCC instead, use the power9le-linux-gnu-vsx.toolchain.cmake toolchain file instead. Note that according to benchmarks, Clang appears to produce noticeably faster CPU inference than GCC for POWER9 targets. For fastest inference, use Clang 18 or higher; earlier versions of Clang may have impaired inference speed due to Bug 49864 and Bug 64664.

For POWER8 instead of POWER9, use the power8le-linux-gnu-vsx.clang.toolchain.cmake or power8le-linux-gnu-vsx.toolchain.cmake toolchain file instead. POWER8 will be slower than POWER9.

Note that the POWER toolchain files only support little-endian mode.

Intel oneAPI

Besides the prerequests in this section, Intel oneAPI BaseKit and HPCKit should be installed. They are available from https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html and https://www.intel.com/content/www/us/en/developer/tools/oneapi/hpc-toolkit.html freely.

Intel oneAPI offers two kinds of compilers, the classic icc/icpc and the LLVM based icx/icpx. To build with these compilers, add CC=icc CXX=icpc or CC=icx CXX=icpx before the cmake command. When compiling with icc/icpc, cmake will warn that xop, avx512, and bf16 extensions are not supported by the compiler, while icx/icpx works well.

Both of these compilers have been tested and passed the ncnn benchmark successfully. The results have been included in ncnn benchmark readme. Generally, icx/icpx are likely to show better performance than icc/icpc and the quantized models can benefit from the extensions icx/icpx supports.

Cross compile: Riscv-gnu-toolchain

Before compiling the whole project, toolchain must be installed. Reference: Riscv-gnu-toolchain build guide

# configure with vector extension.
./configure --prefix=/opt/riscv --enable-multilib --with-arch=rv64gcv

# configure without vector extension.
./configure --prefix=/opt/riscv --enable-multilib --with-arch=rv64gc

# it takes quite a long time:(
sudo make linux

Now you can build the project:

mkdir build-riscv
cd build-riscv
cmake -DDCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=../toolchains/riscv64-unknown-linux-gnu.toolchain.cmake -DNCNN_BUILD_EXAMPLES=ON ..
make -j$(nproc) # or `make -j2` if your cpu isn't powerful enough.

Verification

Verify build by running some examples:

cd ../examples
../build/examples/squeezenet ../images/256-ncnn.png
[0 AMD RADV FIJI (LLVM 10.0.1)]  queueC=1[4]  queueG=0[1]  queueT=0[1]
[0 AMD RADV FIJI (LLVM 10.0.1)]  bugsbn1=0  buglbia=0  bugcopc=0  bugihfa=0
[0 AMD RADV FIJI (LLVM 10.0.1)]  fp16p=1  fp16s=1  fp16a=0  int8s=1  int8a=1
532 = 0.163452
920 = 0.093140
716 = 0.061584

You can also run benchmarks (the 4th argument is a GPU device index to use, refer to vulkaninfo, if you have more than one GPU):

cd ../benchmark
../build/benchmark/benchncnn 10 $(nproc) 0 0
[0 AMD RADV FIJI (LLVM 10.0.1)]  queueC=1[4]  queueG=0[1]  queueT=0[1]
[0 AMD RADV FIJI (LLVM 10.0.1)]  bugsbn1=0  buglbia=0  bugcopc=0  bugihfa=0
[0 AMD RADV FIJI (LLVM 10.0.1)]  fp16p=1  fp16s=1  fp16a=0  int8s=1  int8a=1
num_threads = 4
powersave = 0
gpu_device = 0
cooling_down = 1
          squeezenet  min =    4.68  max =    4.99  avg =    4.85
     squeezenet_int8  min =   38.52  max =   66.90  avg =   48.52
...

To run benchmarks on a CPU, set the 5th argument to -1.

Build for Windows x64 using Visual Studio Community 2017

Download and Install Visual Studio Community 2017 from https://visualstudio.microsoft.com/vs/community/

Start the command prompt: Start → Programs → Visual Studio 2017 → Visual Studio Tools → x64 Native Tools Command Prompt for VS 2017

You can also search x64 Native Tools Command Prompt for VS 2017 directly.

Download protobuf-3.11.2 from https://github.com/google/protobuf/archive/v3.11.2.zip

Build protobuf library:

cd <protobuf-root-dir>
mkdir protobuf_build
cd protobuf_build
cmake -A x64 -DCMAKE_INSTALL_PREFIX=%cd%/install -Dprotobuf_BUILD_TESTS=OFF -Dprotobuf_MSVC_STATIC_RUNTIME=OFF ../cmake
cmake --build . --config Release -j 2
cmake --build . --config Release --target install

(optional) Download and install Vulkan SDK from https://vulkan.lunarg.com/sdk/home

Build ncnn library (replace <protobuf-root-dir> with a proper path):

cd <ncnn-root-dir>
mkdir -p protobuf_build
cd protobuf_build
cmake -A x64 -DCMAKE_INSTALL_PREFIX=%cd%/install -Dprotobuf_DIR=<protobuf-root-dir>/protobuf_build/install/cmake -DNCNN_VULKAN=ON ..
cmake --build . --config Release -j 2
cmake --build . --config Release --target install

Note: To speed up compilation process on multi core machines, configuring cmake to use jom or ninja using -G flag is recommended.

Note: For protobuf >=22.0 (Take v25.3 for example):

Build zlib:

git clone -b -v1.3.1 https://github.com/madler/zlib.git
cd zlib
mkdir build
cd build
cmake -A x64 -DCMAKE_INSTALL_PREFIX=%cd%/install ..
cmake --build . --config Release -j 2
cmake --build . --config Release --target install

Build protobuf library (replace <zlib-root-dir> with a proper path):

git clone -b v25.3 https://github.com/protocolbuffers/protobuf.git
cd protobuf
git submodule update --init --recursive

mkdir protobuf_build
cd protobuf_build
cmake -A x64 -DCMAKE_INSTALL_PREFIX=%cd%/install -DCMAKE_CXX_STANDARD=14 -Dprotobuf_BUILD_TESTS=OFF -Dprotobuf_MSVC_STATIC_RUNTIME=OFF -DZLIB_INCLUDE_DIR=<zlib-root-dir>\build\install\include -DZLIB_LIBRARY=<zlib-root-dir>\build\install\lib\zlib.lib -DABSL_PROPAGATE_CXX_STD=ON ../cmake
cmake --build . --config Release -j 2
cmake --build . --config Release --target install

Build ncnn library (replace <zlib-root-dir> and <protobuf-root-dir> with a proper path):

cd <ncnn-root-dir>
mkdir -p build
cd build
cmake -A x64 -DCMAKE_INSTALL_PREFIX=%cd%/install -DCMAKE_PREFIX_PATH=<protobuf-root-dir>/protobuf_build\install\cmake -DZLIB_INCLUDE_DIR=<zlib-root-dir>\build\install\include -DZLIB_LIBRARY=<zlib-root-dir>\build\install\lib\zlib.lib -Dabsl_DIR=<protobuf-root-dir>/protobuf_build\install\lib\cmake\absl -Dutf8_range_DIR=<protobuf-root-dir>/protobuf_build\install\lib\cmake\utf8_range -DNCNN_VULKAN=ON ..
cmake --build . --config Release -j 2
cmake --build . --config Release --target install

Build for Windows x64 using MinGW-w64

Download MinGW-w64 toolchain from winlibs or w64devkit, add bin folder to environment variables.

Build ncnn library:

cd <ncnn-root-dir>
mkdir build
cd build
cmake -DNCNN_VULKAN=ON -G "MinGW Makefiles" ..
cmake --build . --config Release -j 4
cmake --build . --config Release --target install

Build for macOS

We've published ncnn to brew now, you can just use following method to install ncnn if you have the Xcode Command Line Tools installed.

brew update
brew install ncnn

Or if you want to compile and build ncnn locally, first install Xcode or Xcode Command Line Tools according to your needs.

Then install protobuf and libomp via homebrew

brew install protobuf libomp

Download and install Vulkan SDK from https://vulkan.lunarg.com/sdk/home

wget https://sdk.lunarg.com/sdk/download/1.3.280.1/mac/vulkansdk-macos-1.3.280.1.dmg -O vulkansdk-macos-1.3.280.1.dmg
hdiutil attach vulkansdk-macos-1.3.280.1.dmg
sudo /Volumes/vulkansdk-macos-1.3.280.1/InstallVulkan.app/Contents/MacOS/InstallVulkan --root `pwd`/vulkansdk-macos-1.3.280.1 --accept-licenses --default-answer --confirm-command install
hdiutil detach /Volumes/vulkansdk-macos-1.3.280.1

# setup env
export VULKAN_SDK=`pwd`/vulkansdk-macos-1.3.280.1/macOS
cd <ncnn-root-dir>
mkdir -p build
cd build

cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/ios.toolchain.cmake -DPLATFORM=MAC -DARCHS="x86_64;arm64" \
    -DVulkan_LIBRARY=`pwd`/../vulkansdk-macos-1.3.280.1/macOS/lib/libMoltenVK.dylib \
    -DNCNN_VULKAN=ON -DNCNN_BUILD_EXAMPLES=ON ..

cmake --build . -j 4
cmake --build . --target install

Note: If you encounter libomp related errors during installation, you can also check our GitHub Actions at here to install and use openmp.

Build for ARM Cortex-A family with cross-compiling

Download ARM toolchain from https://developer.arm.com/open-source/gnu-toolchain/gnu-a/downloads

export PATH="<your-toolchain-compiler-path>:${PATH}"

Alternatively install a cross-compiler provided by the distribution (i.e. on Debian / Ubuntu, you can do sudo apt install g++-arm-linux-gnueabi g++-arm-linux-gnueabihf g++-aarch64-linux-gnu).

Depending on your needs build one or more of the below targets.

AArch32 target with soft float (arm-linux-gnueabi)

cd <ncnn-root-dir>
mkdir -p build-arm-linux-gnueabi
cd build-arm-linux-gnueabi
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/arm-linux-gnueabi.toolchain.cmake ..
make -j$(nproc)

AArch32 target with hard float (arm-linux-gnueabihf)

cd <ncnn-root-dir>
mkdir -p build-arm-linux-gnueabihf
cd build-arm-linux-gnueabihf
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/arm-linux-gnueabihf.toolchain.cmake ..
make -j$(nproc)

AArch64 GNU/Linux target (aarch64-linux-gnu)

cd <ncnn-root-dir>
mkdir -p build-aarch64-linux-gnu
cd build-aarch64-linux-gnu
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/aarch64-linux-gnu.toolchain.cmake ..
make -j$(nproc)

Build for Hisilicon platform with cross-compiling

Download and install Hisilicon SDK. The toolchain should be in /opt/hisi-linux/x86-arm

cd <ncnn-root-dir>
mkdir -p build
cd build

# Choose one cmake toolchain file depends on your target platform
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/hisiv300.toolchain.cmake ..
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/hisiv500.toolchain.cmake ..
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/himix100.toolchain.cmake ..
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/himix200.toolchain.cmake ..

make -j$(nproc)
make install

Build for Android

You can use the pre-build ncnn-android-lib.zip from https://github.com/Tencent/ncnn/releases

Download Android NDK from http://developer.android.com/ndk/downloads/index.html and install it, for example:

unzip android-ndk-r21d-linux-x86_64.zip
export ANDROID_NDK=<your-ndk-root-path>

(optional) remove the hardcoded debug flag in Android NDK android-ndk issue

# open $ANDROID_NDK/build/cmake/android.toolchain.cmake for ndk < r23
# or $ANDROID_NDK/build/cmake/android-legacy.toolchain.cmake for ndk >= r23
# delete "-g" line
list(APPEND ANDROID_COMPILER_FLAGS
  -g
  -DANDROID

Build armv7 library

cd <ncnn-root-dir>
mkdir -p build-android-armv7
cd build-android-armv7

cmake -DCMAKE_TOOLCHAIN_FILE="$ANDROID_NDK/build/cmake/android.toolchain.cmake" \
    -DANDROID_ABI="armeabi-v7a" -DANDROID_ARM_NEON=ON \
    -DANDROID_PLATFORM=android-14 -DNCNN_VULKAN=ON ..

# If you use cmake >= 3.21 and ndk-r23
# you need to add -DANDROID_USE_LEGACY_TOOLCHAIN_FILE=False option for working optimization flags

make -j$(nproc)
make install

Pick build-android-armv7/install folder for further JNI usage.

Build aarch64 library:

cd <ncnn-root-dir>
mkdir -p build-android-aarch64
cd build-android-aarch64

cmake -DCMAKE_TOOLCHAIN_FILE="$ANDROID_NDK/build/cmake/android.toolchain.cmake"\
    -DANDROID_ABI="arm64-v8a" \
    -DANDROID_PLATFORM=android-21 -DNCNN_VULKAN=ON ..

# If you use cmake >= 3.21 and ndk-r23
# you need to add -DANDROID_USE_LEGACY_TOOLCHAIN_FILE=False option for working optimization flags

make -j$(nproc)
make install

Pick build-android-aarch64/install folder for further JNI usage.

Build for iOS on macOS with xcode

You can use the pre-build ncnn.framework glslang.framework and openmp.framework from https://github.com/Tencent/ncnn/releases

Install xcode

You can replace -DENABLE_BITCODE=0 to -DENABLE_BITCODE=1 in the following cmake arguments if you want to build bitcode enabled libraries.

Download and install openmp for multithreading inference feature on iPhoneOS

wget https://github.com/llvm/llvm-project/releases/download/llvmorg-11.0.0/openmp-11.0.0.src.tar.xz
tar -xf openmp-11.0.0.src.tar.xz
cd openmp-11.0.0.src

# apply some compilation fix
sed -i'' -e '/.size __kmp_unnamed_critical_addr/d' runtime/src/z_Linux_asm.S
sed -i'' -e 's/__kmp_unnamed_critical_addr/___kmp_unnamed_critical_addr/g' runtime/src/z_Linux_asm.S

mkdir -p build-ios
cd build-ios

cmake -DCMAKE_TOOLCHAIN_FILE=<ncnn-root-dir>/toolchains/ios.toolchain.cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=install \
    -DPLATFORM=OS64 -DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 -DARCHS="arm64;arm64e" \
    -DPERL_EXECUTABLE=/usr/local/bin/perl \
    -DLIBOMP_ENABLE_SHARED=OFF -DLIBOMP_OMPT_SUPPORT=OFF -DLIBOMP_USE_HWLOC=OFF ..

cmake --build . -j 4
cmake --build . --target install

# copy openmp library and header files to xcode toolchain sysroot
# <xcode-dir> is usually /Applications/Xcode.app or /Applications/Xcode-beta.app depends on your Xcode version
sudo cp install/include/* <xcode-dir>/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk/usr/include
sudo cp install/lib/libomp.a <xcode-dir>/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk/usr/lib

Download and install openmp for multithreading inference feature on iPhoneSimulator

wget https://github.com/llvm/llvm-project/releases/download/llvmorg-11.0.0/openmp-11.0.0.src.tar.xz
tar -xf openmp-11.0.0.src.tar.xz
cd openmp-11.0.0.src

# apply some compilation fix
sed -i'' -e '/.size __kmp_unnamed_critical_addr/d' runtime/src/z_Linux_asm.S
sed -i'' -e 's/__kmp_unnamed_critical_addr/___kmp_unnamed_critical_addr/g' runtime/src/z_Linux_asm.S

mkdir -p build-ios-sim
cd build-ios-sim

cmake -DCMAKE_TOOLCHAIN_FILE=<ncnn-root-dir>/toolchains/ios.toolchain.cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=install \
    -DPLATFORM=SIMULATORARM64 -DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 -DARCHS="x86_64;arm64" \
    -DPERL_EXECUTABLE=/usr/local/bin/perl \
    -DLIBOMP_ENABLE_SHARED=OFF -DLIBOMP_OMPT_SUPPORT=OFF -DLIBOMP_USE_HWLOC=OFF ..

cmake --build . -j 4
cmake --build . --target install

# copy openmp library and header files to xcode toolchain sysroot
# <xcode-dir> is usually /Applications/Xcode.app or /Applications/Xcode-beta.app depends on your Xcode version
sudo cp install/include/* <xcode-dir>/Contents/Developer/Platforms/iPhoneSimulator.platform/Developer/SDKs/iPhoneSimulator.sdk/usr/include
sudo cp install/lib/libomp.a <xcode-dir>/Contents/Developer/Platforms/iPhoneSimulator.platform/Developer/SDKs/iPhoneSimulator.sdk/usr/lib

Package openmp framework:

cd <openmp-root-dir>

mkdir -p openmp.framework/Versions/A/Headers
mkdir -p openmp.framework/Versions/A/Resources
ln -s A openmp.framework/Versions/Current
ln -s Versions/Current/Headers openmp.framework/Headers
ln -s Versions/Current/Resources openmp.framework/Resources
ln -s Versions/Current/openmp openmp.framework/openmp
lipo -create build-ios/install/lib/libomp.a build-ios-sim/install/lib/libomp.a -o openmp.framework/Versions/A/openmp
cp -r build-ios/install/include/* openmp.framework/Versions/A/Headers/
sed -e 's/__NAME__/openmp/g' -e 's/__IDENTIFIER__/org.llvm.openmp/g' -e 's/__VERSION__/11.0/g' <ncnn-root-dir>/Info.plist > openmp.framework/Versions/A/Resources/Info.plist

Download and install Vulkan SDK from https://vulkan.lunarg.com/sdk/home

wget https://sdk.lunarg.com/sdk/download/1.2.189.0/mac/vulkansdk-macos-1.2.189.0.dmg?Human=true -O vulkansdk-macos-1.2.189.0.dmg
hdiutil attach vulkansdk-macos-1.2.189.0.dmg
sudo /Volumes/vulkansdk-macos-1.2.189.0/InstallVulkan.app/Contents/MacOS/InstallVulkan --root `pwd`/vulkansdk-macos-1.2.189.0 --accept-licenses --default-answer --confirm-command install
hdiutil detach /Volumes/vulkansdk-macos-1.2.189.0

# setup env
export VULKAN_SDK=`pwd`/vulkansdk-macos-1.2.189.0/macOS

Build library for iPhoneOS:

cd <ncnn-root-dir>
git submodule update --init
mkdir -p build-ios
cd build-ios

cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/ios.toolchain.cmake -DPLATFORM=OS64 -DARCHS="arm64;arm64e" \
    -DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 \
    -DOpenMP_C_FLAGS="-Xclang -fopenmp" -DOpenMP_CXX_FLAGS="-Xclang -fopenmp" \
    -DOpenMP_C_LIB_NAMES="libomp" -DOpenMP_CXX_LIB_NAMES="libomp" \
    -DOpenMP_libomp_LIBRARY="/Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk/usr/lib/libomp.a" \
    -DNCNN_VULKAN=ON -DNCNN_BUILD_BENCHMARK=OFF ..

cmake --build . -j 4
cmake --build . --target install

Build library for iPhoneSimulator:

cd <ncnn-root-dir>
mkdir -p build-ios-sim
cd build-ios-sim

cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/ios.toolchain.cmake -DPLATFORM=SIMULATORARM64 -DARCHS="x86_64;arm64" \
    -DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 \
    -DOpenMP_C_FLAGS="-Xclang -fopenmp" -DOpenMP_CXX_FLAGS="-Xclang -fopenmp" \
    -DOpenMP_C_LIB_NAMES="libomp" -DOpenMP_CXX_LIB_NAMES="libomp" \
    -DOpenMP_libomp_LIBRARY="/Applications/Xcode.app/Contents/Developer/Platforms/iPhoneSimulator.platform/Developer/SDKs/iPhoneSimulator.sdk/usr/lib/libomp.a" \
    -DNCNN_BUILD_BENCHMARK=OFF ..

cmake --build . -j 4
cmake --build . --target install

Package glslang framework for iPhoneOS:

cd <ncnn-root-dir>

mkdir -p glslang.framework/Versions/A/Headers
mkdir -p glslang.framework/Versions/A/Resources
ln -s A glslang.framework/Versions/Current
ln -s Versions/Current/Headers glslang.framework/Headers
ln -s Versions/Current/Resources glslang.framework/Resources
ln -s Versions/Current/glslang glslang.framework/glslang
libtool -static build-ios/install/lib/libglslang.a build-ios/install/lib/libMachineIndependent.a build-ios/install/lib/libGenericCodeGen.a build-ios/install/lib/libSPIRV.a build-ios/install/lib/libOGLCompiler.a build-ios/install/lib/libOSDependent.a -o build-ios/install/lib/libglslang_combined.a
lipo -create build-ios/install/lib/libglslang_combined.a -o glslang.framework/Versions/A/glslang
cp -r build/install/include/glslang glslang.framework/Versions/A/Headers/
sed -e 's/__NAME__/glslang/g' -e 's/__IDENTIFIER__/org.khronos.glslang/g' -e 's/__VERSION__/1.0/g' Info.plist > glslang.framework/Versions/A/Resources/Info.plist

Package ncnn framework for iPhoneOS:

cd <ncnn-root-dir>

mkdir -p ncnn.framework/Versions/A/Headers
mkdir -p ncnn.framework/Versions/A/Resources
ln -s A ncnn.framework/Versions/Current
ln -s Versions/Current/Headers ncnn.framework/Headers
ln -s Versions/Current/Resources ncnn.framework/Resources
ln -s Versions/Current/ncnn ncnn.framework/ncnn
lipo -create build-ios/install/lib/libncnn.a -o ncnn.framework/Versions/A/ncnn
cp -r build-ios/install/include/* ncnn.framework/Versions/A/Headers/
sed -e 's/__NAME__/ncnn/g' -e 's/__IDENTIFIER__/com.tencent.ncnn/g' -e 's/__VERSION__/1.0/g' Info.plist > ncnn.framework/Versions/A/Resources/Info.plist

Pick ncnn.framework glslang.framework and openmp.framework folder for app development.

Build for WebAssembly

Install Emscripten

git clone https://github.com/emscripten-core/emsdk.git
cd emsdk
./emsdk install 3.1.28
./emsdk activate 3.1.28

source emsdk_env.sh

Build without any extension for general compatibility:

mkdir -p build
cd build
cmake -DCMAKE_TOOLCHAIN_FILE=$EMSDK/upstream/emscripten/cmake/Modules/Platform/Emscripten.cmake \
    -DNCNN_THREADS=OFF -DNCNN_OPENMP=OFF -DNCNN_SIMPLEOMP=OFF -DNCNN_SIMPLEOCV=ON -DNCNN_RUNTIME_CPU=OFF -DNCNN_SSE2=OFF -DNCNN_AVX2=OFF -DNCNN_AVX=OFF \
    -DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install

Build with WASM SIMD extension:

mkdir -p build-simd
cd build-simd
cmake -DCMAKE_TOOLCHAIN_FILE=$EMSDK/upstream/emscripten/cmake/Modules/Platform/Emscripten.cmake \
    -DNCNN_THREADS=OFF -DNCNN_OPENMP=OFF -DNCNN_SIMPLEOMP=OFF -DNCNN_SIMPLEOCV=ON -DNCNN_RUNTIME_CPU=OFF -DNCNN_SSE2=ON -DNCNN_AVX2=OFF -DNCNN_AVX=OFF \
    -DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install

Build with WASM Thread extension:

mkdir -p build-threads
cd build-threads
cmake -DCMAKE_TOOLCHAIN_FILE=$EMSDK/upstream/emscripten/cmake/Modules/Platform/Emscripten.cmake \
    -DNCNN_THREADS=ON -DNCNN_OPENMP=ON -DNCNN_SIMPLEOMP=ON -DNCNN_SIMPLEOCV=ON -DNCNN_RUNTIME_CPU=OFF -DNCNN_SSE2=OFF -DNCNN_AVX2=OFF -DNCNN_AVX=OFF \
    -DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install

Build with WASM SIMD and Thread extension:

mkdir -p build-simd-threads
cd build-simd-threads
cmake -DCMAKE_TOOLCHAIN_FILE=$EMSDK/upstream/emscripten/cmake/Modules/Platform/Emscripten.cmake \
    -DNCNN_THREADS=ON -DNCNN_OPENMP=ON -DNCNN_SIMPLEOMP=ON -DNCNN_SIMPLEOCV=ON -DNCNN_RUNTIME_CPU=OFF -DNCNN_SSE2=ON -DNCNN_AVX2=OFF -DNCNN_AVX=OFF \
    -DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install

Pick build-XYZ/install folder for further usage.

Build for AllWinner D1

Download c906 toolchain package from https://www.xrvm.cn/community/download?id=4382928864901402624

tar -xf Xuantie-900-gcc-linux-6.6.0-glibc-x86_64-V3.0.1-20241120.tar.gz
export RISCV_ROOT_PATH=/home/nihui/osd/Xuantie-900-gcc-linux-6.6.0-glibc-x86_64-V3.0.1

Build ncnn with riscv-v vector and simpleocv enabled:

mkdir -p build-c906
cd build-c906
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/c906-v226.toolchain.cmake \
    -DCMAKE_BUILD_TYPE=release -DNCNN_OPENMP=OFF -DNCNN_THREADS=OFF -DNCNN_RUNTIME_CPU=OFF -DNCNN_RVV=OFF -DNCNN_XTHEADVECTOR=ON -DNCNN_ZFH=ON \
    -DNCNN_SIMPLEOCV=ON -DNCNN_BUILD_EXAMPLES=ON ..
cmake --build . -j 4
cmake --build . --target install

Pick build-c906/install folder for further usage.

You can upload binary inside build-c906/examples folder and run on D1 board for testing.

Build for Loongson 2K1000

For gcc version < 8.5, you need to fix msa.h header for workaround msa fmadd/fmsub/maddv/msubv bug.

Open /usr/lib/gcc/mips64el-linux-gnuabi64/8/include/msa.h, find __msa_fmadd and __msa_fmsub and apply changes as the following

// #define __msa_fmadd_w __builtin_msa_fmadd_w
// #define __msa_fmadd_d __builtin_msa_fmadd_d
// #define __msa_fmsub_w __builtin_msa_fmsub_w
// #define __msa_fmsub_d __builtin_msa_fmsub_d
#define __msa_fmadd_w(a, b, c) __builtin_msa_fmadd_w(c, b, a)
#define __msa_fmadd_d(a, b, c) __builtin_msa_fmadd_d(c, b, a)
#define __msa_fmsub_w(a, b, c) __builtin_msa_fmsub_w(c, b, a)
#define __msa_fmsub_d(a, b, c) __builtin_msa_fmsub_d(c, b, a)

find __msa_maddv and __msa_msubv and apply changes as the following

// #define __msa_maddv_b __builtin_msa_maddv_b
// #define __msa_maddv_h __builtin_msa_maddv_h
// #define __msa_maddv_w __builtin_msa_maddv_w
// #define __msa_maddv_d __builtin_msa_maddv_d
// #define __msa_msubv_b __builtin_msa_msubv_b
// #define __msa_msubv_h __builtin_msa_msubv_h
// #define __msa_msubv_w __builtin_msa_msubv_w
// #define __msa_msubv_d __builtin_msa_msubv_d
#define __msa_maddv_b(a, b, c) __builtin_msa_maddv_b(c, b, a)
#define __msa_maddv_h(a, b, c) __builtin_msa_maddv_h(c, b, a)
#define __msa_maddv_w(a, b, c) __builtin_msa_maddv_w(c, b, a)
#define __msa_maddv_d(a, b, c) __builtin_msa_maddv_d(c, b, a)
#define __msa_msubv_b(a, b, c) __builtin_msa_msubv_b(c, b, a)
#define __msa_msubv_h(a, b, c) __builtin_msa_msubv_h(c, b, a)
#define __msa_msubv_w(a, b, c) __builtin_msa_msubv_w(c, b, a)
#define __msa_msubv_d(a, b, c) __builtin_msa_msubv_d(c, b, a)

Build ncnn with mips msa and simpleocv enabled:

mkdir -p build
cd build
cmake -DNCNN_DISABLE_RTTI=ON -DNCNN_DISABLE_EXCEPTION=ON -DNCNN_RUNTIME_CPU=OFF -DNCNN_MSA=ON -DNCNN_MMI=ON -DNCNN_SIMPLEOCV=ON ..
cmake --build . -j 2
cmake --build . --target install

Pick build/install folder for further usage.

You can run binary inside build/examples folder for testing.

Build for Termux on Android

Install app Termux on your phone,and install Ubuntu in Termux.

If you want use ssh, just install openssh in Termux

pkg install proot-distro
proot-distro install ubuntu

or you can see what system can be installed using proot-distro list

while you install ubuntu successfully, using proot-distro login ubuntu to login Ubuntu.

Then make ncnn,no need to install any other dependencies.

git clone https://github.com/Tencent/ncnn.git
cd ncnn
git submodule update --init
mkdir -p build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DNCNN_BUILD_EXAMPLES=ON -DNCNN_PLATFORM_API=OFF -DNCNN_SIMPLEOCV=ON ..
make -j$(nproc)

Then you can run a test

on my Pixel 3 XL using Qualcomm 845,cant load 256-ncnn.png

cd ../examples
../build/examples/squeezenet ../images/128-ncnn.png

Build for QNX

Set QNX environment variables

export QNX_HOST=/opt/qnx710/host/linux/x86_64
export QNX_TARGET=/opt/qnx710/target/qnx7

Create ld link to solve 'cannot find ld' issue

cd ${QNX_HOST}/usr/bin/
ln -s aarch64-unknown-nto-qnx7.1.0-ld ld

Build ncnn with cmake

git clone https://github.com/Tencent/ncnn.git
cd ncnn
git submodule update --init
mkdir -p build-qnx
cd build-qnx
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=../toolchains/qnx710.toolchain.cmake ..
make -j$(nproc)
make install

Pick build-qnx/install folder for further usage.

Build for Nintendo 3DS Homebrew Launcher

Install DevkitPRO toolchains

  • If you are working on windows, download DevkitPro installer from DevkitPro.
  • If you are using Ubuntu, the official guidelines from DevkitPro might not work for you. Try using the lines below to install
sudo apt-get update
sudo apt-get upgrade
wget https://apt.devkitpro.org/install-devkitpro-pacman
chmod +x ./install-devkitpro-pacman
sudo ./install-devkitpro-pacman
export DEVKITPRO=/opt/devkitpro
export DEVKITARM=/opt/devkitpro/devkitARM
export DEVKITPPC=/opt/devkitpro/devkitPPC
export export PATH=$/opt/devkitpro/tools/bin:$PATH
source ~/.profile
sudo dkp-pacman -Sy
sudo dkp-pacman -Syu
sudo dkp-pacman -S 3ds-dev

Copy the toolchain files from 3DS-cmake(DevitARM3DS.cmake and the cmake folder) to NCNN's toolchains folder.

├── toolchains
│   ├── cmake
│   │   ├── bin2s_header.h.in
│   │   ├── FindCITRO3D.cmake
│   │   ├── FindCTRULIB.cmake
│   │   ├── FindFreetype.cmake
│   │   ├── FindJPEG.cmake
│   │   ├── FindPNG.cmake
│   │   ├── FindSF2D.cmake
│   │   ├── FindSFIL.cmake
│   │   ├── FindSFTD.cmake
│   │   ├── FindZLIB.cmake
│   │   ├── LibFindMacros.cmake
│   │   ├── Tools3DS.cmake
│   │   ├── ToolsGBA.cmake
│   │   └── try_add_imported_target.cmake
│   ├── DevkitArm3DS.cmake
...

Build with:

cd ncnn
mkdir build && cd build
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/DevkitArm3DS.cmake .. -DNCNN_SIMPLEOCV=ON -DNCNN_OPENMP=OFF -DNCNN_VFPV4=OFF ..
make -j4
make install

Modify the Makefile in Homebrew example to link and use NCNN in your 3DS Homebrew app.

Build for HarmonyOS with cross-compiling

Download and install HarmonyOS SDK. The sdk installation directory is /opt/ohos-sdk/linux

cd <ncnn-root-dir>
mkdir -p build
cd build

export HM_SDK=/opt/ohos-sdk/linux

# Choose HarmonyOS sdk cmake toolchain file.
# If you want to enable vulkan, set -DNCNN_VULKAN=ON
# The HarmonyOS sdk does not support openmp, use ncnn simpleomp instead.
# Cross-compiling with CMake must use the one provided by the HarmonyOS SDK; otherwise, it won't recognize parameters like OHOS_PLATFORM, leading to compilation errors.
${HM_SDK}/native/build-tools/cmake/bin/cmake -DOHOS_STL=c++_static -DOHOS_ARCH=arm64-v8a -DOHOS_PLATFORM=OHOS -DCMAKE_TOOLCHAIN_FILE=${HM_SDK}/native/build/cmake/ohos.toolchain.cmake -DNCNN_VULKAN=ON -DNCNN_SIMPLEOMP=ON ..

make -j$(nproc)
make install

Build for ESP32 with cross-compiling

Download esp-idf sdk

git clone https://github.com/espressif/esp-idf
cd esp-idf
git submodule update --init --recursive

Install esp-idf sdk and configure the environment

sudo sh install.sh
source export.sh

Note: python>=3.8, cmake>=3.24.0

Build ncnn library:

mkdir build-esp32
cd build-esp32
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/esp32.toolchain.cmake -DCMAKE_BUILD_TYPE=Release ..
make -j 4
make install

Note: Make sure to compile in esp-idf environment.

The compiled ncnn library and headers can be put to the esp32 project to test.

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