Parallel GENESIS for Large-Scale Modeling

Nigel H. Goddard; Greg Hood

doi:10.1007/978-1-4757-9800-5_141

Parallel GENESIS for Large-Scale Modeling

Nigel H. Goddard, Greg Hood

School of Informatics

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Simulations of computational models are limited in size and speed by the power and capacity of the computational platform. We have parallelized the GENESIS object-oriented neural simulator [1] for networked workstations, multiprocessors and massively parallel supercomputers. These can provide two orders of magnitude increase in the size of the models that can be effectively simulated. As larger models are partitioned across many processors, interprocessor communication can limit the effective speedup obtainable. This suggests two classes of problems that may benefit most from parallel simulation: parameter searching and network models.

Original language	English
Title of host publication	Computational Neuroscience
Subtitle of host publication	Trends in Research, 1997
Editors	James M. Bower
Place of Publication	Boston, MA
Publisher	Springer
Pages	911-917
Number of pages	7
ISBN (Electronic)	978-1-4757-9800-5
ISBN (Print)	978-1-4757-9802-9
DOIs	https://doi.org/10.1007/978-1-4757-9800-5_141
Publication status	Published - 1997

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Parallel GENESIS for Large-Scale Modeling

Abstract

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