通信学报2017，Vol.38Issue(11)：171-177,7.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
Accelerated computational implementation of reconciliation for continuous variable quantum key distribution on GPU
摘要
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 2×105 continuous 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.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Key words
continuous variable quantum key distribution/reconciliation/low density parity check code/static linked list/GPU decoding分类
信息技术与安全科学引用本文复制引用
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):171-177,7.基金项目
山西省国际科技合作计划基金资助项目(No.2014081027-1) （No.2014081027-1）
山西省基础研究基金资助项目(No.2014011007-2) （No.2014011007-2）
山西省回国留学人员科研基金资助项目(No.2014-012) International Technology Cooperation Program of Shanxi Province (No.2014081027-1),The Basic Research Program of Shanxi Province (No.2014011007-2),Research Project Supported by Shanxi Scholarship Council of China (No.2014-012) （No.2014-012）
