Accelerated computational implementation of reconciliation for continuous variable quantum key distribution on GPU
For the low computing speed of reconciliation for current continuous variable quantum key distribution， CPU＆amp;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 efficienc...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2017-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017222/ |
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| Summary: | For the low computing speed of reconciliation for current continuous variable quantum key distribution， CPU＆amp;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 2×10<sup>5</sup>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. |
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| ISSN: | 1000-436X |