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基于GPU的LDPC增强准最大似然译码器并行实现
引用本文:孔飞跃,蒋学芹,万雪芬,陈思井,崔剑,杨义.基于GPU的LDPC增强准最大似然译码器并行实现[J].计算机工程,2020,46(5):207-215.
作者姓名:孔飞跃  蒋学芹  万雪芬  陈思井  崔剑  杨义
作者单位:东华大学信息科学与技术学院,上海201620;华北科技学院河北省物联网监控工程技术研究中心,河北廊坊065201;华北科技学院计算机学院,河北廊坊065201;武汉船舶通信研究所,武汉430205;北京航空航天大学网络空间安全学院,北京100083
基金项目:工程技术研究中心项目;廊坊市科学技术研究与发展计划;河北省重点研发计划;国家重点研发计划
摘    要:增强准最大似然(EQML)译码器对于码长较短的低密度奇偶校验(LDPC)码的译码性能优于传统置信传播(BP)译码器,可较好满足5G移动通信的高可靠性要求,但由于其计算结构复杂导致译码速度大幅降低。为提高EQML译码器的译码速度,提出一种基于GPU的EQML译码器并行化加速方案,压缩并存储不规则LDPC码的奇偶校验矩阵,通过对传统BP译码算法进行重新排序以最大化利用Kernel中的线程,并对再处理过程中的每个阶段进行多码字并行译码,实现内存访问优化及流并行译码。实验结果表明,基于GPU的EQML译码器在保持纠错性能的同时,相比基于CPU的EQML译码器的译码速度约提升了2个数量级。

关 键 词:低密度奇偶校验码  GPU并行译码  增强准最大似然译码器  置信传播译码器  现场可编程门阵列

Parallel Implementation of GPU-Based LDPC Enhanced Quasi-Maximum Likelihood Decoder
KONG Feiyue,JIANG Xueqin,WAN Xuefen,CHEN Sijing,CUI Jian,YANG Yi.Parallel Implementation of GPU-Based LDPC Enhanced Quasi-Maximum Likelihood Decoder[J].Computer Engineering,2020,46(5):207-215.
Authors:KONG Feiyue  JIANG Xueqin  WAN Xuefen  CHEN Sijing  CUI Jian  YANG Yi
Affiliation:(College of Information Science and Technology,Donghua University,Shanghai 201620,China;Hebei IoT Monitoring Engineering Technology Research Center,North China Institute of Science and Technology,Langfang,Hebei 065201,China;College of Computer,North China Institute of Science and Technology,Langfang,Hebei 065201,China;Wuhan Maritime Communication Research Institute,Wuhan 430205,China;School of Cyber Science and Technology,Beihang University,Beijing 100083,China)
Abstract:The Enhanced Quasi-Maximum Likelihood(EQML)decoder has better decoding performance for short Low Density Parity Check(LDPC)codes than traditional Belief Propagation(BP)decoder,and can meet the high reliability requirements of 5G mobile communication.However,its decoding speed is greatly reduced due to its complex computational structure.To address the problem,this paper proposes a parallel acceleration scheme based on Graphics Processing Unit(GPU)for EQML decoder.The scheme compresses and stores the parity check matrix of irregular LDPC codes,and resorts the traditional BP decoding algorithms to maximize the utilization of threads in Kernel.Then parallel decoding is implemented for multi-code words in each stage of reprocessing,so as to realize memory access optimization and parallel decoding of streams.Experimental results show that the GPU-based EQML decoder improves the speed by two orders of magnitude compared with the CPU-based decoder,while keeping the error correction performance.
Keywords:Low Density Parity Check(LDPC)code  GPU parallel decoding  Enhanced Quasi-Maximum Likelihood(EQML)decoder  Belief Propagation(BP)decoder  Field Programmable Gate Array(FPGA)
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