This API supports the following video stream formats for Linux and Windows platforms: MPEG-2, VC-1, and H.264 (AVCHD). The CPU will still be used for: Video decoding (If hardware decoding is turned off or unavailable). The actual hardware decode can run on either Video Processor (VP) or CUDA hardware, depending on the hardware capabilities and the codecs. HandBrake supports the NVIDIA NVENC encoder and NVDEC encoder. nvcodec cudaupload, Filter/Video, Uploads data into NVIDA GPU via CUDA APIs nvautogpuh264enc, Codec/Encoder/Video/Hardware, Encode H.264 video streams using. The NVIDIA CUDA Video Decoder (NVCUVID) API gives developers access to hardware video decoding capabilities on NVIDIA GPUs with CUDA. It is compliant with AVC/H.264 (MPEG‐4 Part 10 AVC, This may mean that the package is missing, has been obsoleted, or is only. The NVIDIA CUDA Video Encoder (NVCUVENC) API enables developers to efficiently process H.264 video encoding on NVIDIA GPUs with CUDA. nvidianvidia-desktop: sudo apt install nvidia-cuda-toolkit sudo password for nvidia: Reading package lists Done Building dependency tree Reading state information Done Package nvidia-cuda-toolkit is not available, but is referred to by another package. The APIs and documentation are available as part of the CUDA SDK Code Samples. NVIDIA provides video encoding and decoding APIs as part of the CUDA SDK to enable system and software developers to accelerate performance on NVIDIA GPUs with CUDA. Please contact MainConcept for more information on the CUDA H.264/AVC Encoder SDK. The MainConcept CUDA H.264/AVC Encoder supports any NVIDIA GPU with CUDA compute capability 1.1 and later for transcoding. Using the MainConcept CUDA H.264/AVC Encoder SDK, the entire H.264/AVC transcoding process is done on NVIDIA GPUs, except for entropy encoding which is done on the CPU. It allows transcoding from MPEG-2, VC-1, H.264/AVC elementary streams, and raw frames into the H.264/AVC Baseline and Main Profile formats. The MainConcept™ CUDA H.264/AVC Encoder SDK enables developers of video applications and system solutions to take advantage of the parallel processing power of NVIDIA GPUs to deliver much faster video encoding than possible on CPUs alone. Video input in YUV formats are taken as input (either CPU system or GPU memory) and video output frames are encoded to an H. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. CUDA Video Encode (C Library) API This sample demonstrates how to effectively use the CUDA Video Encoder API encode H.264 video. To help you develop powerful applications without having to re-implement the essential algorithms, NVIDIA and its partners provide solutions to get you up and being productive at lighting speeds. The NVIDIA CUDA Toolkit provides a development environment for creating high performance GPU-accelerated applications. The CUDA architecture has the performance to do amazing video and media processing. Video Processing Software Solutions for NVIDIA Developers
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |