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基于OpenCL/GPU异构计算的高速数据协调系统设计

A System Design for High-Speed Data Reconciliation Based on OpenCL/GPU Heterogeneous Computing

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摘要

针对当前连续变量量子密钥分发时数据协调运算速度低的问题,本文提出一种采用GPU与OpenCL异构计算的多维数据协调方案,并提出了一种静态双向十字链表存储超大规模LDPC码的校验矩阵,以适应OpenCL平台特殊要求。实验仿真结果显示,当码长为2×105时,在保证有效数据协调且相同码率的前提下,GPU平均译码速率可达到CPU的4.2倍,但牺牲了部分精度。

Abstract

For the problem of low speed of data reconciliation in the current continuous-variable quantum key distribution, this paper proposes a multi-dimensional data reconciliation scheme based on GPU and OpenCL heterogeneous computing. Moreover, we fatherly propose a static two-way cross-linked list storage hyperscale LDPC check matrix to meet the special requirements of the OpenCL′s special regulations. Experimental simulation results show that when the code length is 2×105, under the premise of ensuring effective data reconciliation in same code rate, the average decoding rate of the GPU can reach 4.2 times that of the CPU at the expense of sacrificing some precision.

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中图分类号:O431;TN914

DOI:10.3788/jqo20192503.0302

所属栏目:量子信息科学与技术

基金项目:山西省基础研究项目(201801D121118)

收稿日期:2019-03-06

修改稿日期:2019-04-17

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作者单位    点击查看

贺超:山西大学 物理电子工程学院,太原 030006
郭大波:山西大学 物理电子工程学院,太原 030006
穆健健:山西大学 物理电子工程学院,太原 030006
马识途:山西大学 物理电子工程学院,太原 030006

联系人作者:贺超(790525697@qq.com)

备注:贺超(1994-),男,硕士研究生,山西大同人,主要从事量子密钥分发方面的研究。

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引用该论文

HE Chao,GUO Da-bo,MU Jian-jian,MA Shi-tu. A System Design for High-Speed Data Reconciliation Based on OpenCL/GPU Heterogeneous Computing[J]. Acta Sinica Quantum Optica, 2019, 25(3): 273-281

贺超,郭大波,穆健健,马识途. 基于OpenCL/GPU异构计算的高速数据协调系统设计[J]. 量子光学学报, 2019, 25(3): 273-281

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