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A Parallel Algorithm for Enumerating Joint Weight of a Binary Linear Code in Network Coding

Shohei Ando, Fumihiko Ino, Toru Fujiwara, and Kenichi Hagihara
Graduate School of Information Science and Technology, Osaka University
2nd International Symposium on Networking and Computing (CANDAR 2014), 2014

@article{ando2014parallel,

   title={A Parallel Algorithm for Enumerating Joint Weight of a Binary Linear Code in Network Coding},

   author={Ando, Shohei and Ino, Fumihiko and Fujiwara, Toru and Hagihara, Kenichi},

   year={2014}

}

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In this paper, we present a parallel algorithm for enumerating joint weight of a binary linear (n, k) code, aiming at accelerating assessment of its decoding error probability for network coding. To reduce the number of pairs of codewords to be investigated, our parallel algorithm reduces dimension k by focusing on the all-one vector included in many practical codes. We also employ a population count instruction to compute joint weight of codewords with a less number of instructions. Our algorithm is implemented on a multi-core CPU system and an NVIDIA GPU system using OpenMP and compute unified device architecture (CUDA), respectively. We apply our implementation to a subcode of a (127,22) BCH code to evaluate the impact of acceleration.
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