如何建立NVEnc

by rigaya

Windows
Linux (Ubuntu 22.04 - 23.04)
Linux (Ubuntu 20.04)
Linux (Ubuntu 18.04)
Linux (Fedora 33)

Windows

0. 环境需求

要构建NVEnc，需要以下组件。

Visual Studio 2019
CUDA 10.1 或更高版本 (x64)
CUDA 11.0 或更高版本 (x86)
Avisynth SDK
VapourSynth SDK

1. 安装构建工具

使用sdk安装Avisynth+和VapourSynth。

然后，Avisynth+ SDK 的 "avisynth_c.h" 和VapourSynth SDK 的 "VapourSynth.h" 应被添加到 Visual Studio 的包含路径中。

这些包含路径可以通过环境变量"AVISYNTH_SDK"和"VAPOURSYNTH_SDK"来传递。

使用默认安装，环境变量可以设置如下。

setx AVISYNTH_SDK "C:\Program Files (x86)\AviSynth+\FilterSDK"
setx VAPOURSYNTH_SDK "C:\Program Files (x86)\VapourSynth\sdk"

2. 下载源代码

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
curl -s -o ffmpeg_lgpl.7z -L https://github.com/rigaya/ffmpeg_dlls_for_hwenc/releases/download/20231123/ffmpeg_dlls_for_hwenc_20231123.7z
7z x -offmpeg_lgpl -y ffmpeg_lgpl.7z

3. 构建 NVEncC.exe / NVEnc.auo

最后，打开 NVEnc.sln，然后开始使用 Visual Studio 构建 NVEnc。

	For Debug build	For Release build
NVEncC(64).exe	DebugStatic	RelStatic
NVEnc.auo (win32 only)	Debug	Release
cufilters.auf (win32 only)	DebugFilters	RelFilters

Linux (Ubuntu 22.04 - 23.04)

0. 环境需求

GPU 驱动版本 435.21 或更高
支持 C++17 标准的编译器
CUDA 10/11
git
所需的库:
- ffmpeg 4.x/5.x libs (libavcodec*, libavformat*, libavfilter*, libavutil*, libswresample*, libavdevice*)
- libass9
- [可选] AvisynthPlus
- [可选] VapourSynth

1. 安装构建工具

sudo apt install build-essential git

2. 安装 NVIDIA 驱动

3. 安装 CUDA

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install --no-install-recommends cuda-toolkit
export CUDA_PATH=/usr/local/cuda

4. 安装所需的库

安装ffmpeg和其他需要的库

sudo apt install ffmpeg \
  libavcodec-extra libavcodec-dev libavutil-dev libavformat-dev libswresample-dev libavfilter-dev libavdevice-dev \
  libass-dev

5. [可选] 安装 AvisynthPlus

只有在需要支持 AvisynthPlus(avs) reader 时才需要安装AvisynthPlus

如果不需要avs reader，请跳转到 [7. 构建 NVEncC]

如何构建 AvisynthPlus

5.1 安装 AvisynthPlus 的构建工具

sudo apt install cmake

5.2 安装 AvisynthPlus

git clone https://github.com/AviSynth/AviSynthPlus.git
cd AviSynthPlus
mkdir avisynth-build && cd avisynth-build 
cmake ../
make && sudo make install
cd ../..

6. [可选] 安装 VapourSynth

只有在需要支持 VapourSynth(vpy) reader 时才需要安装 VapourSynth

如果不需要 vpy reader，请跳转到 [7. 构建 NVEncC]

如何构建 VapourSynth

6.1 安装 VapourSynth 的构建工具

sudo apt install python3-pip cython3 autoconf automake libtool meson libzimg-dev

6.2 安装 VapourSynth

git clone https://github.com/vapoursynth/vapoursynth.git
cd vapoursynth
./autogen.sh
./configure
make && sudo make install

# Make sure vapoursynth could be imported from python
# Change "python3.x" depending on your environment
sudo ln -s /usr/local/lib/python3.x/site-packages/vapoursynth.so /usr/lib/python3.x/lib-dynload/vapoursynth.so
sudo ldconfig

6.3 检查 VapourSynth 是否正确安装

确认得到了版本号且没有产生报错

LD_LIBRARY_PATH=/usr/local/lib vspipe --version

7. 构建 NVEncC

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
./configure
make

检查是否正常执行

./nvencc --check-hw

应可以得到当前NVENC支持的编解码器列表

NVEnc (x64) 7.24 (r2526) by rigaya, Apr 28 2023 14:52:09 (gcc 12.2.0/Linux)
  [NVENC API v12.0, CUDA 12.1]
 reader: raw, y4m, avs, vpy, avsw, avhw [H.264/AVC, H.265/HEVC, MPEG2, VP8, VP9, VC-1, MPEG1, MPEG4, AV1]
#0: NVIDIA GeForce RTX 4080 (9728 cores, 2505 MHz)[2147483.64]
Avaliable Codec(s)
H.264/AVC
H.265/HEVC
AV1

Linux (Ubuntu 20.04)

0. 环境需求

GPU 驱动版本 435.21 或更高
支持 C++17 标准的编译器
CUDA 10/11
git
所需的库:
- ffmpeg 4.x libs (libavcodec58, libavformat58, libavfilter7, libavutil56, libswresample3, libavdevice58)
- libass9
- [可选] AvisynthPlus
- [可选] VapourSynth

1. 安装构建工具

sudo apt install build-essential git

2. 安装 NVIDIA 驱动

获取可安装的驱动程序版本

ubuntu-drivers devices

应可以获得以下输出

== /sys/devices/pci0000:00/0000:00:03.1/0000:0d:00.0 ==
modalias : pci:v000010DEd00001B80sv000019DAsd00001426bc03sc00i00
vendor   : NVIDIA Corporation
model    : GP104 [GeForce GTX 1080]
driver   : nvidia-driver-390 - distro non-free
driver   : nvidia-driver-460 - distro non-free recommended
driver   : nvidia-driver-450-server - distro non-free
driver   : nvidia-driver-418-server - distro non-free
driver   : nvidia-driver-450 - distro non-free
driver   : xserver-xorg-video-nouveau - distro free builtin

选择安装最新版本的驱动

sudo apt install nvidia-driver-460
sudo reboot

重启后，检查驱动是否正确安装

rigaya@rigaya6-linux:~$ nvidia-smi
Sun Feb 21 13:49:17 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 1080    Off  | 00000000:0D:00.0  On |                  N/A |
|  0%   33C    P8     8W / 230W |     46MiB /  8111MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1076      G   /usr/lib/xorg/Xorg                 36MiB |
|    0   N/A  N/A      1274      G   /usr/bin/gnome-shell                7MiB |
+-----------------------------------------------------------------------------+

3. 安装 CUDA

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install --no-install-recommends cuda-toolkit
export CUDA_PATH=/usr/local/cuda

4. 安装所需的库

安装ffmpeg和其他需要的库

sudo apt install ffmpeg \
  libavcodec-extra libavcodec-dev libavutil-dev libavformat-dev libswresample-dev libavfilter-dev libavdevice-dev \
  libass9 libass-dev

5. [可选] 安装 AvisynthPlus

只有在需要支持 AvisynthPlus(avs) reader 时才需要安装AvisynthPlus

如果不需要avs reader，请跳转到 [7. 构建 NVEncC]

如何构建 AvisynthPlus

5.1 安装 AvisynthPlus 的构建工具

sudo apt install cmake

5.2 安装 AvisynthPlus

git clone https://github.com/AviSynth/AviSynthPlus.git
cd AviSynthPlus
mkdir avisynth-build && cd avisynth-build 
cmake ../
make && sudo make install
cd ../..

5.3 [可选] 安装 lsmashsource

# Install lsmash
git clone https://github.com/l-smash/l-smash.git
cd l-smash
./configure --enable-shared
make && sudo make install
cd ..
 
# Install vslsmashsource
git clone https://github.com/HolyWu/L-SMASH-Works.git
cd L-SMASH-Works
# Use older version to meet libavcodec lib version requirements
git checkout -b 20200531 refs/tags/20200531
cd VapourSynth
meson build
cd build
ninja && sudo ninja install
cd ../../../

6. [可选] 安装 VapourSynth

只有在需要支持 VapourSynth(vpy) reader 时才需要安装 VapourSynth

如果不需要 vpy reader，请跳转到 [7. 构建 NVEncC]

如何构建 VapourSynth

6.1 安装 VapourSynth 的构建工具

sudo apt install python3-pip autoconf automake libtool meson

6.2 安装 zimg

git clone https://github.com/sekrit-twc/zimg.git --recursive
cd zimg
./autogen.sh
./configure
make && sudo make install
cd ..

6.3 安装 cython

sudo pip3 install Cython

6.4 安装 VapourSynth

git clone https://github.com/vapoursynth/vapoursynth.git
cd vapoursynth
./autogen.sh
./configure
make && sudo make install

# Make sure vapoursynth could be imported from python
# Change "python3.x" depending on your environment
sudo ln -s /usr/local/lib/python3.x/site-packages/vapoursynth.so /usr/lib/python3.x/lib-dynload/vapoursynth.so
sudo ldconfig

6.5 检查 VapourSynth 是否正确安装

确认得到了版本号且没有产生报错

LD_LIBRARY_PATH=/usr/local/lib vspipe --version

6.6 [可选] 构建 vslsmashsource

# Install lsmash
git clone https://github.com/l-smash/l-smash.git
cd l-smash
./configure --enable-shared
make && sudo make install
cd ..
 
# Install vslsmashsource
git clone https://github.com/HolyWu/L-SMASH-Works.git
cd L-SMASH-Works
# Use older version to meet libavcodec lib version requirements
git checkout -b 20200531 refs/tags/20200531
cd VapourSynth
meson build
cd build
ninja && sudo ninja install
cd ../../../

7. 构建 NVEncC

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
./configure
make

检查是否正常执行

./nvencc --check-hw

应可以得到当前NVENC支持的编解码器列表

#0: GeForce GTX 1080 (2560 cores, 1822 MHz)[PCIe3x16][460.32]
Avaliable Codec(s)
H.264/AVC
H.265/HEVC

Linux (Ubuntu 18.04)

0. 所需环境

GPU 驱动版本 435.21 或更高
支持 C++17 标准的编译器
CUDA 10
git
所需的库:
- ffmpeg 4.x libs (libavcodec58, libavformat58, libavfilter7, libavutil56, libswresample3, libavdevice58)
- libass9
- [可选] VapourSynth

1. 安装构建工具

sudo apt install git g++-8

2. 安装 NVIDIA 驱动和 CUDA 10.2

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget http://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-2-local-10.2.89-440.33.01/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda
export CUDA_PATH=/usr/local/cuda

重启后，检查驱动是否已正确安装(在AWS g3s.xlarge中测试)

$ nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01    Driver Version: 440.33.01    CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla M60           On   | 00000000:00:1E.0 Off |                    0 |
| N/A   28C    P8    15W / 150W |      0MiB /  7618MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

3. 安装所需的库

安装 ffmpeg 4.x 库

sudo add-apt-repository ppa:jonathonf/ffmpeg-4
sudo apt update
sudo apt install ffmpeg \
  libavcodec-extra58 libavcodec-dev libavutil56 libavutil-dev libavformat58 libavformat-dev libavdevice58 libavdevice-dev \
  libswresample3 libswresample-dev libavfilter-extra7 libavfilter-dev libass9 libass-dev

4. [可选] 安装 VapourSynth

只有在需要支持 VapourSynth(vpy) reader 时才需要安装 VapourSynth

如果不需要 vpy reader，请跳转到 [6. 构建 NVEncC]

如何构建 VapourSynth

4.1 安装 VapourSynth 的构建工具

sudo apt install python3-pip autoconf automake libtool meson

4.2 安装 zimg

git clone https://github.com/sekrit-twc/zimg.git --recursive
cd zimg
./autogen.sh
./configure
make && sudo make install
cd ..

4.3 安装 cython

sudo pip3 install Cython

4.4 安装 VapourSynth

git clone https://github.com/vapoursynth/vapoursynth.git
cd vapoursynth
./autogen.sh
./configure
make && sudo make install

# Make sure vapoursynth could be imported from python
# Change "python3.x" depending on your environment
sudo ln -s /usr/local/lib/python3.x/site-packages/vapoursynth.so /usr/lib/python3.x/lib-dynload/vapoursynth.so
sudo ldconfig

4.5 检查 VapourSynth 是否已正确安装

Make sure you get version number without errors.

vspipe --version

4.6 [可选] 构建 vslsmashsource

# Install lsmash
git clone https://github.com/l-smash/l-smash.git
cd l-smash
./configure --enable-shared
make && sudo make install
cd ..
 
# Install vslsmashsource
git clone https://github.com/HolyWu/L-SMASH-Works.git
cd L-SMASH-Works/VapourSynth
meson build
cd build
ninja && sudo ninja install
cd ../../../

5. 构建 NVEncC

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
./configure --cxx=g++-8
make

检查是否正确执行

./nvencc --check-hw

应可以得到当前NVENC支持的编解码器列表 (在AWS g3s.xlarge进行测试)

#0: Tesla M60 (2048 cores, 1177 MHz)[PCIe3x16][440.33]
Avaliable Codec(s)
H.264/AVC
H.265/HEVC

Linux (Fedora 33)

0. 所需环境

支持 C++17 标准的编译器
CUDA 11
git
所需的库:
- ffmpeg 4.x libs (libavcodec58, libavformat58, libavfilter7, libavutil56, libswresample3, libavdevice58)
- libass9
- [可选] AvisynthPlus
- [可选] VapourSynth

1. 安装构建工具

sudo dnf install @development-tools

2. 准备安装 CUDA 和 NVIDIA driver

sudo dnf update
sudo dnf upgrade
sudo dnf clean all
sudo dnf install kernel-devel
sudo dnf install make pciutils acpid libglvnd-devel
sudo dnf install dkms

3. 安装 CUDA 和 NVIDIA driver

安装 CUDA 和包括在 CUDA package 中的 NVIDIA driver

wget https://developer.download.nvidia.com/compute/cuda/11.2.1/local_installers/cuda-repo-fedora33-11-2-local-11.2.1_460.32.03-1.x86_64.rpm
sudo rpm -ivh cuda-repo-fedora33-11-2-local-11.2.1_460.32.03-1.x86_64.rpm
sudo dnf clean all
sudo dnf install cuda
reboot

CUDA 会安装在 /usr/local/cuda.

重启后，检查驱动是否已正确安装

$ nvidia-smi
Sun Mar  7 14:27:45 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 1080    Off  | 00000000:0D:00.0 Off |                  N/A |
|  0%   27C    P8     7W / 230W |     65MiB /  8111MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1335      G   /usr/libexec/Xorg                  56MiB |
|    0   N/A  N/A      1476      G   /usr/bin/gnome-shell                6MiB |
+-----------------------------------------------------------------------------+

4. 安装所需的库

安装ffmpeg和其他所需的库

sudo dnf install https://download1.rpmfusion.org/free/fedora/rpmfusion-free-release-$(rpm -E %fedora).noarch.rpm
sudo dnf install ffmpeg ffmpeg-devel libass libass-devel

5. [可选] 安装 AvisynthPlus

只有在需要支持 AvisynthPlus(avs) reader 时才需要安装AvisynthPlus

如果不需要avs reader，请跳转到 [7. 构建 NVEncC]

如何构建 AvisynthPlus

5.1 安装 AvisynthPlus 的构建工具

sudo dnf install cmake

5.2 安装 AvisynthPlus

git clone git://github.com/AviSynth/AviSynthPlus.git
cd AviSynthPlus
mkdir avisynth-build && cd avisynth-build 
cmake ../
make && sudo make install
cd ../..

5.3 [可选] 安装 lsmashsource

# Build lsmash
git clone https://github.com/l-smash/l-smash.git
cd l-smash
./configure --enable-shared
make && sudo make install
cd ..

# Build lsmashsource
git clone https://github.com/HolyWu/L-SMASH-Works.git
cd L-SMASH-Works
git checkout -b 20200531 refs/tags/20200531
cd AviSynth
meson build
cd build
ninja && sudo ninja install
cd ../../../

6. [可选] 安装 VapourSynth

只有在需要支持 VapourSynth(vpy) reader 时才需要安装 VapourSynth

如果不需要 vpy reader，请跳转到 [7. 构建 NVEncC]

如何构建 VapourSynth

6.1 安装 VapourSynth 的构建工具

sudo dnf install zimg zimg-devel meson autotools automake libtool python3-devel ImageMagick

6.2 安装 VapourSynth

sudo pip3 install Cython --install-option="--no-cython-compile"

6.3 构建 VapourSynth

git clone https://github.com/vapoursynth/vapoursynth.git
cd vapoursynth
./autogen.sh
./configure
make && sudo make install

# Make sure vapoursynth could be imported from python
# Change "python3.x" depending on your environment
sudo ln -s /usr/local/lib/python3.x/site-packages/vapoursynth.so /usr/lib/python3.x/lib-dynload/vapoursynth.so
sudo ldconfig

6.4 Check if VapourSynth has been installed properly

确认得到了版本号且没有产生报错

vspipe --version

6.5 [可选] 构建 vslsmashsource

# Build lsmash (Not required if already done in 5.3)
git clone https://github.com/l-smash/l-smash.git
cd l-smash
./configure --enable-shared
make && sudo make install
cd ..
 
# Build vslsmashsource
git clone https://github.com/HolyWu/L-SMASH-Works.git
cd L-SMASH-Works
git checkout -b 20200531 refs/tags/20200531
cd VapourSynth
meson build
cd build
ninja && sudo ninja install
cd ../../../

7. 构建 NVEncC

git clone https://github.com/rigaya/NVEnc --recursive
cd NVEnc
./configure
make

检查是否正常执行

./nvencc --check-hw

应可以得到当前NVENC支持的编解码器列表

#0: GeForce GTX 1080 (2560 cores, 1822 MHz)[PCIe3x16][460.32]
Avaliable Codec(s)
H.264/AVC
H.265/HEVC

Files

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如何建立NVEnc

Windows

0. 环境需求

1. 安装构建工具

2. 下载源代码

3. 构建 NVEncC.exe / NVEnc.auo

Linux (Ubuntu 22.04 - 23.04)

0. 环境需求

1. 安装构建工具

2. 安装 NVIDIA 驱动

3. 安装 CUDA

4. 安装所需的库

5. [可选] 安装 AvisynthPlus

5.1 安装 AvisynthPlus 的构建工具

5.2 安装 AvisynthPlus

6. [可选] 安装 VapourSynth

6.1 安装 VapourSynth 的构建工具

6.2 安装 VapourSynth

6.3 检查 VapourSynth 是否正确安装

7. 构建 NVEncC

Linux (Ubuntu 20.04)

0. 环境需求

1. 安装构建工具

2. 安装 NVIDIA 驱动

3. 安装 CUDA

4. 安装所需的库

5. [可选] 安装 AvisynthPlus

5.1 安装 AvisynthPlus 的构建工具

5.2 安装 AvisynthPlus

5.3 [可选] 安装 lsmashsource

6. [可选] 安装 VapourSynth

6.1 安装 VapourSynth 的构建工具

6.2 安装 zimg

6.3 安装 cython

6.4 安装 VapourSynth

6.5 检查 VapourSynth 是否正确安装

6.6 [可选] 构建 vslsmashsource

7. 构建 NVEncC

Linux (Ubuntu 18.04)

0. 所需环境

1. 安装构建工具

2. 安装 NVIDIA 驱动和 CUDA 10.2

3. 安装所需的库

4. [可选] 安装 VapourSynth

4.1 安装 VapourSynth 的构建工具

4.2 安装 zimg

4.3 安装 cython

4.4 安装 VapourSynth

4.5 检查 VapourSynth 是否已正确安装

4.6 [可选] 构建 vslsmashsource

5. 构建 NVEncC

Linux (Fedora 33)

0. 所需环境

1. 安装构建工具

2. 准备安装 CUDA 和 NVIDIA driver

3. 安装 CUDA 和 NVIDIA driver

4. 安装所需的库

5. [可选] 安装 AvisynthPlus

5.1 安装 AvisynthPlus 的构建工具

5.2 安装 AvisynthPlus

5.3 [可选] 安装 lsmashsource

6. [可选] 安装 VapourSynth

6.1 安装 VapourSynth 的构建工具

6.2 安装 VapourSynth

6.3 构建 VapourSynth

6.4 Check if VapourSynth has been installed properly

6.5 [可选] 构建 vslsmashsource

7. 构建 NVEncC