Parallelizing the cascade-correlation algorithm using time warp

Autor:	Paul L. Springer, Sandeep Gulati
Rok vydání:	1995
Předmět:	Speedup Artificial neural network Parallel processing (DSP implementation) Artificial Intelligence Event (computing) Computer science Cognitive Neuroscience Cascade correlation algorithm Benchmark (computing) Process (computing) Parallel algorithm Parallel computing
Zdroj:	Neural Networks. 8:571-577
ISSN:	0893-6080
DOI:	10.1016/0893-6080(94)00103-s
Popis:	This paper discusses the method in which the cascade-correlation algorithm was parallelzznd in such a way that it could be run using the Time Warp Operating System (TWOS). TWOS is a special-purpose operating system designed to run parallel discrete event simulations with maximum efficiency on parallel or distributed computers. The parallelization process is described, and a formula is derived for the maximum possible speedup using this technique. For the benchmark used, a speedup of 8 was obtained while running on 10 nodes of a BBN GP1000 parallel computer, indicating that this approach is a useful way of parallelizing cascade-correlation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::88d9df44def2a7d1556aa132dd27b96e https://doi.org/10.1016/0893-6080(94)00103-s Zobrazit plný text záznamu Full Text from ScienceDirect