基于SIMD的AVS3并行率失真优化量化算法

唐毅欣; 黄晓峰; 唐然; 周洋; 崔燕; 殷海兵

doi:10.11959/j.issn.1000-0801.2024155

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基于SIMD的AVS3并行率失真优化量化算法

研究与开发 | 更新时间：2024-08-05

- 基于SIMD的AVS3并行率失真优化量化算法
- SIMD-based parallelized rate distortion optimized quantization for AVS3
- 电信科学 2024年40卷第6期页码：114-126
- 作者机构：
  
  1.杭州电子科技大学通信工程学院，浙江杭州 310018
  2.浙江省经济信息中心，浙江杭州 310006
- 作者简介：
  
  [ "唐毅欣（2003- ），女，杭州电子科技大学通信工程学院在读，主要研究方向为视频编解码。" ]
  [ "黄晓峰（1988- ），男，博士，杭州电子科技大学通信工程学院副教授，主要研究方向为数字视频编解码与芯片架构设计。" ]
  [ "唐然（1996- ），男，杭州电子科技大学通信工程学院硕士生，主要研究方向为视频编解码。" ]
  [ "周洋（1979- ），男，杭州电子科技大学通信工程学院副教授，主要研究方向为基于机器学习的视频图像处理、3D视频编解码。" ]
  [ "崔燕（1988- ），女，浙江省经济信息中心高级工程师，主要研究方向为视频编解码。" ]
  [ "殷海兵（1974- ），男，博士，杭州电子科技大学通信工程学院教授、在站博士后，主要研究方向为数字视频编解码、多媒体信号处理、芯片结构设计验证。" ]
- 基金信息：
  
  国家科技重大专项(2021ZD0109802);国家自然科学基金资助项目(61901150)
- DOI：10.11959/j.issn.1000-0801.2024155
  中图分类号： TN919.81
- 收稿：2024-01-27，
  
  修回：2024-04-08，
  
  纸质出版：2024-06-20
- 稿件说明：
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唐毅欣,黄晓峰,唐然等.基于SIMD的AVS3并行率失真优化量化算法[J].电信科学,2024,40(06):114-126.

TANG Yixin,HUANG Xiaofeng,TANG Ran,et al.SIMD-based parallelized rate distortion optimized quantization for AVS3[J].Telecommunications Science,2024,40(06):114-126.
唐毅欣,黄晓峰,唐然等.基于SIMD的AVS3并行率失真优化量化算法[J].电信科学,2024,40(06):114-126. DOI： 10.11959/j.issn.1000-0801.2024155.

TANG Yixin,HUANG Xiaofeng,TANG Ran,et al.SIMD-based parallelized rate distortion optimized quantization for AVS3[J].Telecommunications Science,2024,40(06):114-126. DOI： 10.11959/j.issn.1000-0801.2024155.

摘要

针对第三代音频视频标准（the third generation audio video coding standard，AVS3）中的率失真优化量化（rate-distortion optimization quantization，RDOQ）过程的编码效率问题，提出一种基于单指令多数据（single instruction multiple data，SIMD）的并行RDOQ算法。首先，在最优系数决策（optimal coefficient decision，OCD）阶段，通过优化，仅保留扫描线内的依赖关系。然后，在最后一个非零位置决策（last non-zero position decision，LNPD）阶段，基于分治策略，通过将Zig-Zag扫描线分解成多个独立扫描线，实现每条扫描线上最优系数位置的并行计算。最后，采用SIMD指令进行并行加速，以提高整个率失真优化量化的计算效率。实验结果表明，该算法在AI配置下，可以降低29.46%的编码时间，而BD-Rate仅损失0.25%。

Abstract

To improve the coding efficiency of rate-distortion optimization quantization (RDOQ) for the third-generation audio video coding standard (AVS3)

a parallelized RDOQ algorithm based on single instruction multiple data (SIMD) was proposed. Firstly

in the optimal coefficient decision (OCD) stage

the dependencies within the scan line were retained through optimization. Secondly

in the last non-zero position decision (LNPD) stage

the Zig-Zag scan line was split into various independent lines based on the partitioning strategy. The optimal coefficients on each scan line were allowed to be calculated in parallel by the proposed method. Finally

SIMD instructions were utilized for parallelized acceleration to boost calculation efficiency in the RDOQ process. Experimental results show that the proposed algorithm can achieve a 29.46% coding time reduction with only 0.25% BD-Rate loss for AI configuration.

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references

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