1673-159X

CN 51-1686/N

耗尽型脉冲神经P系统的矩阵表示及GPU实现

Matrix Representation and GPU Implementation for Spiking Neural P System with Exhaustive Use of Rules

  • 摘要: 各类P系统并行计算的实现是膜计算的一个研究热点。针对耗尽型脉冲神经P系统, 提出了其并行计算的矩阵表示, 并以此为基础研究了耗尽型脉冲神经P系统的GPU实现。仿真实验分析了耗尽型脉冲神经P系统的并行计算在GPU上的加速性能, 在10次实验中, GPU对CPU的平均加速比为1.4。

     

    Abstract: The realization of parallel computing for all kinds of P systems is the research hot point for membrane computing.Matrix representation for spiking neural P system with exhaustive use of rules is proposed in this paper.With the completion of the matrix representation, the authors research the GPU implementation of the spiking neural P system with exhaustive use of rules.The parallel computing simulation of the spiking neural P system with exhaustive use of rules gives the acceleration performance on GPUs.In ten times experiments, the average acceleration ratio of GPU to CPU is 1.4.

     

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