2014 Second International Symposium on Computing and Networking (CANDAR) (2014)
Dec. 10, 2014 to Dec. 12, 2014
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 code words 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 code words with a less number of instructions. Our algorithm is implemented on a multi-core CPU system and an NVIDIA GPU system using Open MP and compute unified device architecture (CUDA), respectively. We apply our implementation to a sub code of a (127,22) BCH code to evaluate the impact of acceleration.
Joints, Histograms, Vectors, Graphics processing units, Parallel algorithms, Instruction sets, Acceleration
S. Ando, F. Ino, T. Fujiwara and K. Hagihara, "A Parallel Algorithm for Enumerating Joint Weight of a Binary Linear Code in Network Coding," 2014 Second International Symposium on Computing and Networking (CANDAR), Shizuoka, Japan, 2014, pp. 137-143.