Simulation of neural networks on a massively parallel computer (DAP-510) using sparse matrix techniques

[1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation Pub Date : 1990-10-08 DOI:10.1109/FMPC.1990.89486

S.N. Gupta, M. Zubair, C. Grosch

引用次数: 3

Abstract

A parallel sparse matrix algorithm is proposed for the simulation of the modified Hopfield-Tank (MHT) network for solving the Traveling Salesman Problem (TSP). The MHT network using this sparse matrix algorithm has been implemented on a DAP-510, a massively parallel SIMD (single-instruction-steam, multiple-data-stream) computer consisting of 1024 processors. Problems of various sizes, ranging from eight cities up to 256 cities, have been simulated. The results show a very large speedup for the algorithm as compared with one using a standard dense matrix implementation.<>

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利用稀疏矩阵技术在大规模并行计算机(DAP-510)上模拟神经网络

针对改进Hopfield-Tank (MHT)网络求解旅行商问题(TSP)，提出了一种并行稀疏矩阵算法。使用这种稀疏矩阵算法的MHT网络已经在DAP-510上实现，DAP-510是由1024个处理器组成的大规模并行SIMD(单指令蒸汽，多数据流)计算机。模拟了不同规模的问题，从8个城市到256个城市不等。结果表明，与使用标准密集矩阵实现的算法相比，该算法有非常大的加速

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

[1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation

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