![]() Hardware acceleration dramatically improves the performance of the workflow. Using the FFmpeg library is common practice when transcoding video data. Separate from the CUDA cores, NVENC/NVDEC run encoding or decoding workloads without slowing the execution of graphics or CUDA workloads running at the same time. Hardware accelerated transcoding with FFmpeg An up-to-date support matrix can be found at the Video Encode and Decode Support Matrix page. Actual support depends on the GPU that is used. Figure 1 lists many of the codecs, format and features supported with current NVIDIA hardware. NVENC and NVDEC support the many important codecs for encoding and decoding. NVIDIA GPUs ship with an on-chip hardware encoder and decoder unit often referred to as NVENC and NVDEC. 在nv-codec-headers目录下执行git checkout sdk/9.0,切换回旧版本后,make clean之后重新编译ffmpeg即可。 NVIDIA Encoding and Decoding Hardware configure -prefix="$HOME/local" -pkg-config-flags="-static" -extra-cflags="-I$HOME/local/include" -extra-ldflags="-L$HOME/local/lib" -extra-libs=-lpthread -extra-libs=-lm -bindir="$HOME/local/bin" -enable-gpl -enable-libfdk_aac -enable-libmp3lame -enable-libx264 -enable-nonfree -enable-gpl -enable-cuda -enable-cuvid -enable-nvdec -enable-nvenc -enable-libnpp -extra-cflags=-I/usr/local/cuda/include -extra-ldflags=-L/usr/local/cuda/lib64įfmpeg -vsync 0 -hwaccel cuda -hwaccel_output_format cuda -i test.mp4 -c:a copy -vf scale_npp=1280:720 -c:v h264_nvenc -b:v 5M output/re5.mp4īugfix: Driver does not support the required nvenc API version. PKG_CONFIG_PATH="$HOME/local/lib/pkgconfig".
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