update build tutorial for d1 and ls2k

README.md

@@ -63,7 +63,7 @@ ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架
 
 ### HowTo
 
-**[how to build ncnn library](https://github.com/Tencent/ncnn/wiki/how-to-build) on Linux / Windows / MacOS / Raspberry Pi3 / Android / NVIDIA Jetson / iOS / WebAssembly**
+**[how to build ncnn library](https://github.com/Tencent/ncnn/wiki/how-to-build) on Linux / Windows / MacOS / Raspberry Pi3 / Android / NVIDIA Jetson / iOS / WebAssembly / AllWinner D1 / Loongson 2K1000**
 
 * [Build for Linux / NVIDIA Jetson / Raspberry Pi3](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-linux)
 * [Build for Windows x64 using VS2017](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-windows-x64-using-visual-studio-community-2017)
@@ -73,6 +73,8 @@ ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架
 * [Build for Android](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-android)
 * [Build for iOS on MacOS with xcode](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-ios-on-macos-with-xcode)
 * [Build for WebAssembly](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-webassembly)
+* [Build for AllWinner D1](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-allwinner-d1)
+* [Build for Loongson 2K1000](https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-loongson-2k1000)
 
 **[download prebuild binary package for android and ios](https://github.com/Tencent/ncnn/releases)**
 

docs/how-to-build/how-to-build.md

@@ -14,6 +14,8 @@ $ git submodule update --init
 * [Build for Android](#build-for-android)
 * [Build for iOS on MacOS with xcode](#build-for-ios-on-macos-with-xcode)
 * [Build for WebAssembly](#build-for-webassembly)
+* [Build for AllWinner D1](#build-for-allwinner-d1)
+* [Build for Loongson 2K1000](#build-for-loongson-2k1000)
 
 ***
 
@@ -555,3 +557,54 @@ cmake --build . --target install
 ```
 
 Pick `build-XYZ/install` folder for further usage.
+
+***
+
+### Build for AllWinner D1
+
+Download c906 toolchain package from https://occ.t-head.cn/community/download?id=3913221581316624384
+
+```shell
+tar -xf riscv64-linux-x86_64-20210512.tar.gz
+export RISCV_ROOT_PATH=/home/nihui/osd/riscv64-linux-x86_64-20210512
+```
+
+Build ncnn with riscv-v vector and simpleocv enabled:
+```shell
+mkdir -p build-c906
+cd build-c906
+cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/c906.toolchain.cmake \
+    -DCMAKE_BUILD_TYPE=relwithdebinfo -DNCNN_OPENMP=OFF -DNCNN_THREADS=OFF -DNCNN_RUNTIME_CPU=OFF -DNCNN_RVV=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 bug.
+
+Open ```/usr/lib/gcc/mips64el-linux-gnuabi64/8/include/msa.h```, find ```__msa_fmadd_w``` and apply changes as the following
+```c
+// #define __msa_fmadd_w __builtin_msa_fmadd_w
+#define __msa_fmadd_w(a, b, c) __builtin_msa_fmadd_w(c, b, a)
+```
+
+Build ncnn with mips msa and simpleocv enabled:
+```shell
+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.