Biao Wang, M. Alvarez-Mesa, C. C. Chi, B. Juurlink, D. Souza, A. Ilic, N. Roma, L. Sousa
{"title":"高效HEVC解码器的异构CPU与GPU系统","authors":"Biao Wang, M. Alvarez-Mesa, C. C. Chi, B. Juurlink, D. Souza, A. Ilic, N. Roma, L. Sousa","doi":"10.1109/MMSP.2016.7813353","DOIUrl":null,"url":null,"abstract":"The High Efficiency Video Coding (HEVC) standard provides higher compression efficiency than other video coding standards but at the cost of increased computational load, which makes it hard to achieve real-time encoding/decoding of high-resolution, high-quality video sequences. In this paper, we investigate how Graphics Processing Units (GPUs) can be employed to accelerate HEVC decoding. GPUs are known to provide massive processing capability for throughput computing kernels, but the HEVC entropy decoding kernel cannot be executed efficiently on GPUs. We therefore propose a complete HEVC decoding solution for heterogeneous CPU+GPU systems, in which the entropy decoder is executed on the CPU and the remaining kernels on the GPU. Furthermore, the decoder is pipelined such that the CPU and the GPU can decode different frames in parallel. The proposed CPU+GPU decoder achieves an average frame rate of 150 frames per second for Ultra HD 4K video sequences when four CPU cores are used with an NVIDIA GeForce Titan X GPU.","PeriodicalId":113192,"journal":{"name":"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Efficient HEVC decoder for heterogeneous CPU with GPU systems\",\"authors\":\"Biao Wang, M. Alvarez-Mesa, C. C. Chi, B. Juurlink, D. Souza, A. Ilic, N. Roma, L. Sousa\",\"doi\":\"10.1109/MMSP.2016.7813353\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The High Efficiency Video Coding (HEVC) standard provides higher compression efficiency than other video coding standards but at the cost of increased computational load, which makes it hard to achieve real-time encoding/decoding of high-resolution, high-quality video sequences. In this paper, we investigate how Graphics Processing Units (GPUs) can be employed to accelerate HEVC decoding. GPUs are known to provide massive processing capability for throughput computing kernels, but the HEVC entropy decoding kernel cannot be executed efficiently on GPUs. We therefore propose a complete HEVC decoding solution for heterogeneous CPU+GPU systems, in which the entropy decoder is executed on the CPU and the remaining kernels on the GPU. Furthermore, the decoder is pipelined such that the CPU and the GPU can decode different frames in parallel. The proposed CPU+GPU decoder achieves an average frame rate of 150 frames per second for Ultra HD 4K video sequences when four CPU cores are used with an NVIDIA GeForce Titan X GPU.\",\"PeriodicalId\":113192,\"journal\":{\"name\":\"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMSP.2016.7813353\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2016.7813353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
摘要
HEVC (High Efficiency Video Coding)标准提供了比其他视频编码标准更高的压缩效率,但其代价是计算量的增加,这使得高分辨率、高质量视频序列的实时编码/解码难以实现。在本文中,我们研究如何使用图形处理器(gpu)来加速HEVC解码。众所周知,gpu为吞吐量计算内核提供了大量的处理能力,但HEVC熵解码内核无法在gpu上高效执行。因此,我们提出了一种完整的HEVC解码解决方案,用于异构CPU+GPU系统,其中熵解码器在CPU上执行,其余内核在GPU上执行。此外,解码器是流水线的,这样CPU和GPU可以并行解码不同的帧。当四个CPU内核与NVIDIA GeForce Titan X GPU一起使用时,所提出的CPU+GPU解码器实现了每秒150帧的超高清4K视频序列的平均帧率。
Efficient HEVC decoder for heterogeneous CPU with GPU systems
The High Efficiency Video Coding (HEVC) standard provides higher compression efficiency than other video coding standards but at the cost of increased computational load, which makes it hard to achieve real-time encoding/decoding of high-resolution, high-quality video sequences. In this paper, we investigate how Graphics Processing Units (GPUs) can be employed to accelerate HEVC decoding. GPUs are known to provide massive processing capability for throughput computing kernels, but the HEVC entropy decoding kernel cannot be executed efficiently on GPUs. We therefore propose a complete HEVC decoding solution for heterogeneous CPU+GPU systems, in which the entropy decoder is executed on the CPU and the remaining kernels on the GPU. Furthermore, the decoder is pipelined such that the CPU and the GPU can decode different frames in parallel. The proposed CPU+GPU decoder achieves an average frame rate of 150 frames per second for Ultra HD 4K video sequences when four CPU cores are used with an NVIDIA GeForce Titan X GPU.