前言,公司转码集群服务器资源有限,需要考虑GPU方案,本文记录下整个实现ffmpeg gpu 转码的过程。
该文章后续仍在不断的更新修改中, 请移步到原文地址http://dmwan.cc
环境:
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=16.04
DISTRIB_DESCRIPTION="Ubuntu 16.04.1 LTS"
注意,这里机器启动级别调低,不要加载桌面系统。
本机是2核4G 普通硬盘,gpu 型号:GTX950M
第一部分,安装cuda 8:
1.1 查看是否有显卡:
lspci | grep -i nvidia
1.2 查看操作系统是否cuda 官方支持:
uname -m && cat /etc/*release
1.3 安装gcc g++ 等编译依赖基础库
apt-get install gcc g++ build-essential
1.4 下载安装cuda
下载cuda:
wget --no-check-certificate https://developer.nvidia.com/compute/cuda/8.0/prod/local_installers/cuda-repo-ubuntu1604-8-0-local_8.0.44-1_amd64-deb
安装 cuda 源:
dpkg -i cuda-repo-ubuntu1604-8-0-local_8.0.44-1_amd64-deb
添加源:
deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /
更新缓存:
apt-get update
安装cuda:
apt-get install cuda
1.5 设置环境变量
export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
source ~/.bashrc
1.6 安装官方示例并验证环境
查看驱动信息:
cat /proc/driver/nvidia/version
安装官方示例:
cuda-install-samples-8.0.sh ./
跑下示例:
cd NVIDIA_CUDA-8.0_Samples/bin/x86_64/linux/release && ./deviceQuery
输出下面内容 Pass为安装成功:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 1080"
CUDA Driver Version / Runtime Version 8.0 / 8.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 8112 MBytes (8506179584 bytes)
(20) Multiprocessors, (128) CUDA Cores/MP: 2560 CUDA Cores
GPU Max Clock rate: 1734 MHz (1.73 GHz)
Memory Clock rate: 5005 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 2097152 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 2 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 3 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GTX 1080
Result = PASS
第二部分,安装ffmpeg
2.1 安装基础依赖:
apt-get update
apt-get -y install autoconf automake build-essential libass-dev libfreetype6-dev \
libsdl2-dev libtheora-dev libtool libva-dev libvdpau-dev libvorbis-dev libxcb1-dev libxcb-shm0-dev \
libxcb-xfixes0-dev pkg-config texinfo zlib1g-dev
2.2 安装yasm
apt-get install yasm #版本为1.3
2.3 安装lib264
apt-get install libx264-dev #版本为148
2.4 安装libx265(显卡不一定支持265编码)
apt-get install libx265-dev
2.5 安装 libvpx
apt-get install libvpx-dev #版本为1.5
2.6 安装 安装libfdk-aac
apt-get install libfdk-aac-dev # 无版本要求
2.7 安装libmp3lam
apt-get install libmp3lame-dev
2.8 安装libopus
apt-get install libopus-dev # 1.1.2
第三部分,安装NVENC:
3.1 安装依赖:
sudo apt-get -y install glew-utils libglew-dbg libglew-dev libglew1.13 \
libglewmx-dev libglewmx-dbg freeglut3 freeglut3-dev freeglut3-dbg libghc-glut-dev \
libghc-glut-doc libghc-glut-prof libalut-dev libxmu-dev libxmu-headers libxmu6 \
libxmu6-dbg libxmuu-dev libxmuu1 libxmuu1-dbg
3.2 下载ffmpeg
git clone https://github.com/FFmpeg/FFmpeg ffmpeg -b master
3.3 下载nvidia video sdk
下载地址:https://developer.nvidia.com/nvidia-video-codec-sdk#Download,这里版本8.0, 解压后命名为 nv_sdk, 与ffmpeg 放于同文件夹。
3.4 移动头文件
cp -r nv_sdk/LegacySamples/common/inc/ /usr/include/
第四部分,编译ffmpeg
编译命令如下:
export PKG_CONFIG_PATH=/usr/lib/x86_64-linux-gnu/pkgconfig
PATH="$HOME/bin:$PATH" ./configure \
--bindir="$HOME/bin" \
--enable-gpl \
--enable-libass \
--enable-libfdk-aac \
--enable-libfreetype \
--enable-libmp3lame \
--enable-libopus \
--enable-libtheora \
--enable-libvorbis \
--enable-libvpx \
--enable-libx264 \
--enable-libx265 \
--enable-nonfree \
--extra-cflags=-I../nv_sdk \
--extra-ldflags=-L../nv_sdk \
--extra-cflags="-I/usr/local/cuda/include/" \
--extra-ldflags=-L/usr/local/cuda/lib64 \
--disable-shared \
--enable-nvenc \
--enable-cuda \
--enable-cuvid \
--enable-libnpp
PATH="$HOME/bin:$PATH" make -j$(nproc)
make -j$(nproc) install
make -j$(nproc) distclean
hash -r
第五部分,转码测试:
ffmpeg -i input.flv -c:v h264_nvenc -c:a aac output.mp4
倍速对比,同样硬件条件下,gpu 提速在7-8倍左右。
frame=21022 fps=398 q=21.0 Lsize= 232698kB time=00:14:36.75 bitrate=2174.2kbits/s dup=137 drop=0 speed=16.6x
播放试了下播放效果,和cpu 播放无明显差别。