指纹图像比较系统的并行算法性能

Proceedings of SPDP '96: 8th IEEE Symposium on Parallel and Distributed Processing Pub Date : 1996-10-23 DOI:10.1109/SPDP.1996.570362

H. Ammar, Zhouhui Miao

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引用次数: 0

摘要

本文研究了基于神经网络的指纹图像比对(FIC)系统训练过程中并行算法的性能分析问题。假设目标体系结构为粗粒度分布式内存并行体系结构。研究了两种类型的并行性:节点并行性和训练集并行性。这些算法在32节点CM-5上实现。给出了理论分析和实验结果，比较了这些算法的性能。

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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Performance of parallel algorithms for a fingerprint image comparison system

This paper addresses the problem of analyzing the performance of parallel algorithms for the training procedure of a neural network based fingerprint image comparison (FIC) system. The target architecture is assumed to be a coarse-grain distributed memory parallel architecture. Two types of parallelism: node parallelism and training set parallelism (TSP) are investigated. These algorithms are implemented on a 32 node CM-5. Theoretical analysis and experimental results comparing the performance of these algorithms are presented.

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Proceedings of SPDP '96: 8th IEEE Symposium on Parallel and Distributed Processing

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