Hadamard变换改进HEVC使用英特尔AVX-512

Jackson Teh Ka Sing, Usman Ullah Sheikh, M. Mokji, N. Alias
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引用次数: 0

摘要

高效视频编码(HEVC)在不牺牲图像质量的前提下,将数据压缩比(MPEG-AVC/H.264)提高了一倍。然而,这种优越的压缩是以更多的计算负载为代价的,从而导致更长的编码和解码时间。本文提出了对HEVC数据进行矢量化的重计算算法,即Hadamard变换或绝对变换差和(SATD)和绝对差和(SAD),以实现优化的压缩性能。单指令多数据(SIMD)加速将基于英特尔AVX-512(高级矢量扩展)指令集架构(ISA)。由于HEVC支持更多的编码树块(CTB)大小,因此与AVC相比,SATD和SAD算法最终会变得更加复杂。因此,具有不同块大小的SATD和SAD算法将受到SIMD加速的影响。我们在HEVC SATD和SAD上提供了基于不同SIMD ISA和没有SIMD实现的性能评估,并发现AVX-512优化实现与未优化的SATD和SAD相比执行速度更快,但与SSE优化的SATD和SAD相比表现出性能降低的迹象。
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Hadamard Transform Improvement for HEVC using Intel AVX-512
High Efficiency Video Coding (HEVC) doubles the data compression ratio compared to previous generation compression technology, Moving Picture Expert Group-Advanced Video Codec (MPEG-AVC/H.264) without sacrificing the image quality. However, this superior compression comes at the cost of more computation payload resulting in longer time for encoding and decoding. This work proposes the vectorization on HEVC data heavy computation algorithm, Hadamard Transform or Sum of Absolute Transform Difference (SATD) and Sum of Absolute Difference (SAD) to achieve optimized compression performance. Single Instruction Multiple Data (SIMD) acceleration will be based on the Intel AVX-512 (Advanced Vector Extension) Instruction Set Architecture (ISA). Since HEVC supports more coding tree block (CTB) sizes, SATD and SAD algorithms eventually become more complex compared to AVC. As a result, SATD and SAD algorithms with various block sizes will be subjected to SIMD acceleration. We provide performance evaluation based on different SIMD ISA and without SIMD implementation on HEVC SATD and SAD and found that AVX-512 optimized implementation performed faster when compared to non- optimized SATD and SAD but showed signs of reduced performance when compared to SSE optimized SATD and SAD.
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