连续变量量子密钥分发数据协调加速运算的GPU实现

doi:10.11959/j.issn.1000-436x.2017222

通信学报 ›› 2017, Vol. 38 ›› Issue (11): 171-177.doi: 10.11959/j.issn.1000-436x.2017222

连续变量量子密钥分发数据协调加速运算的GPU实现

刘绍婷,王晓凯,郭大波

山西大学物理电子工程学院，山西太原 030006

修回日期:2017-07-04 出版日期:2017-11-01 发布日期:2017-12-13
作者简介:刘绍婷（1991-），女，山西吕梁人，山西大学硕士生，主要研究方向为量子密钥分发。|王晓凯（1963-），男，山西运城人，博士，山西大学教授，主要研究方向为通信网络管理、控制与优化等。|郭大波（1963-），男，山西阳泉人，博士，山西大学副教授，主要研究方向为量子密钥分发。
基金资助:
山西省国际科技合作计划基金资助项目(2014081027-1);山西省基础研究基金资助项目(2014011007-2);山西省回国留学人员科研基金资助项目(2014-012)

Accelerated computational implementation of reconciliation for continuous variable quantum key distribution on GPU

Shao-ting LIU,Xiao-kai WANG,Da-bo GUO

College of Physics and Electronic Engineering,Shanxi University,Taiyuan 030006,China

Revised:2017-07-04 Online:2017-11-01 Published:2017-12-13
Supported by:
International Technology Cooperation Program of Shanxi Province(2014081027-1);The Basic Research Program of Shanxi Province(2014011007-2);Research Project Supported by Shanxi Scholarship Council of China(2014-012)

摘要/Abstract

摘要：

针对当前连续变量量子密钥分发系统数据协调运算速度低等问题，用GPU实现了基于LDPC的SEC协议下数据协调算法的并行化加速运算，提出用静态双向十字链表的方法高效存储大规模稀疏校验矩阵，从而保证在不牺牲协调效率的前提下提高了译码速率。仿真实验结果表明，在信道信噪比为4.9 dB以上、2×10⁵个连续变量序列可靠协调以及协调效率为91.71%的情况下，基于Geforce GT 650 MB的GPU和2.5 GHz、8 GB内存的CPU硬件平台，译码速率可达16.4 kbit/s，相对于仅CPU平台，计算速度提高15倍以上。

关键词: 连续变量量子密钥分发, 数据协调, 低密度奇偶码, 静态链表, GPU译码

Abstract:

For the low computing speed of reconciliation for current continuous variable quantum key distribution， CPU&GPU-parallel reconciliation algorithms was designed based on LDPC of SEC protocol to speed up decoding computing.In order to raise decoding speed without sacrifice reconciliation efficiency,a static two-way cross linked list to efficiently store large scale sparse parity matrix was employed.The simulation experimental results show that the speed of the decoding rate reaches 16.4 kbit/s when the channel SNR is over 4.9 dB and the reliability of the 2×10⁵continuous variable quantum sequence,with reconciliation efficiency of 91.71%.The experimental based on the Geforce GT 650 MB GPU and the 2.5 GHz and 8 GB memory CPU hardware platform.Relative to the only CPU platform,computing speed increased by more than 15 times.

Key words: continuous variable quantum key distribution, reconciliation, low density parity check code, static linked list,GPU decoding

中图分类号:

TN918.91

刘绍婷,王晓凯,郭大波. 连续变量量子密钥分发数据协调加速运算的GPU实现[J]. 通信学报, 2017, 38(11): 171-177.

Shao-ting LIU,Xiao-kai WANG,Da-bo GUO. Accelerated computational implementation of reconciliation for continuous variable quantum key distribution on GPU[J]. Journal on Communications, 2017, 38(11): 171-177.

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参考文献 17

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地址	排序	索引
A[0]	2	6
A[1]	4	2
A[2]	5	7
A[3]	8	NULL
A[4]	1	0
A[5]	7	3
A[6]	3	1
A[7]	6	5

方案	码长	每一级码率	收敛信噪比R_SN/dB	100次迭代的时间/s	译码速率/(kbit·s^?1)	协调效率
GPU并行	200 000	0/0/0.3/0.95	4.9	12.28	16.4	0.917 1
仅CPU	200 000	0/0/0.3/0.95	4.9	185.76	1.07	0.917 1
上海交大^[5]	10 000	未报道	未报道	未报道	25 000	—

连续变量量子密钥分发数据协调加速运算的GPU实现

Accelerated computational implementation of reconciliation for continuous variable quantum key distribution on GPU

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