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

Abstract

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 2×105continuous 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.

Keywords

• continuous variable quantum key distribution;reconciliation;low density parity check code;static linked list
• GPU decoding