基于GPU的H.264并行解码算法  

H.264 Parallel Decoding Algorithm Based on GPU

作　　者：陈鹏[1] 曹剑炜[1] 陈庆奎[1] 

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《计算机工程》2014年第1期283-286,共4页Computer Engineering

基　　金：国家自然科学基金资助项目(60970012);教育部博士学科点专项科研博导基金资助项目(20113120110008);上海市教委科研创新基金资助重点项目(13ZZ112);上海信息技术领域重点科技攻关计划基金资助项目(09511501000;09220502800);上海市教育科学研究基金资助项目(B11042);上海市一流学科基金资助项目(XTKX2012)

摘　　要：针对并行处理H.264标准视频流解码问题,提出基于CPU/GPU的协同运算算法。以统一设备计算架构(CUDA)语言作为GPU编程模型,实现DCT逆变换与帧内预测在GPU中的加速运算。在保持较高计算精度的前提下,结合CUDA混合编程,提高系统的计算性能。利用NIVIDIA提供的CUDA语言,在解码过程中使DCT逆变换和帧内预测在GPU上并行实现,将并行算法与CPU单机实现进行比较,并用不同数量的视频流验证并行解码算法的加速效果。实验结果表明,该算法可大幅提高视频流的编解码效率,比CPU单机的平均计算加速比提高10倍。In terms of parallel decoding H.264 video stream problems, this paper builds CPU/GPU cooperative computing model to accelerate video encoding and decoding computing. This model uses Compute Unified Device Architecture（CUDA） language as GPU programming model, proposes and implements DCT inverse conversation and intra-frame prediction in a GPU accelerated computing. In the premise of maintaining higher calculation accuracy, combined with CUDA mixed programming, improves the computational performance of the system greatly. The algorithm uses CUDA language provided by NVIDIA, and realizes the DCT inverse conversation and intra-frame prediction on GPU. The experiment compares the parallel algorithm and the sole CPU, and verifies the accelerating effect of the parallel decoding algorithm by using different number of video streams. Experimental result shows that this system improves the video streaming codec efficiency, and it can accelerate 10 times faster than the average CPU sole calculation.

关 键 词：统一设备计算架构 并行运算 H 264标准 DCT逆变换 帧内预测 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]