{"title":"生物神经微电路在多核系统上的仿真","authors":"I. Muntean, M. Joldos","doi":"10.1109/CISIS.2012.196","DOIUrl":null,"url":null,"abstract":"Our research focuses on the identification and quantification of the impact that multi-core parallelization strategies have on the stability of the result of spiking neural networks simulations. We investigated Open MP-based implementations of the Spike Response Model and Spike Time-Dependent Plasticity for studying behaviors of biological neurons and synapses. The underlying neural microcircuits have small-world topologies. The simulation strategy is a synchronous one. The software development methodology we follow makes use of systematic unit testing and continuous integration, giving us a way to verify various perturbations of simulation results. We carried out investigations on systems having different multi-core processors. The processing speed (spikes/second) of our simulator scales well with the number of cores, but the parallel efficiency is moderate when all cores of the system are used in the simulation (0.57 for 12 cores e.g.). The primary outcomes of this work are twofold: One the one hand, the proposed parallel simulation strategies show a dynamic behavior unaltered by the use of multi-core specific technologies. On the other hand, we analyze issues met in our approach to multi-core simulations.","PeriodicalId":158978,"journal":{"name":"2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Simulation of Biological Neural Microcircuits on Multi-core Systems\",\"authors\":\"I. Muntean, M. Joldos\",\"doi\":\"10.1109/CISIS.2012.196\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our research focuses on the identification and quantification of the impact that multi-core parallelization strategies have on the stability of the result of spiking neural networks simulations. We investigated Open MP-based implementations of the Spike Response Model and Spike Time-Dependent Plasticity for studying behaviors of biological neurons and synapses. The underlying neural microcircuits have small-world topologies. The simulation strategy is a synchronous one. The software development methodology we follow makes use of systematic unit testing and continuous integration, giving us a way to verify various perturbations of simulation results. We carried out investigations on systems having different multi-core processors. The processing speed (spikes/second) of our simulator scales well with the number of cores, but the parallel efficiency is moderate when all cores of the system are used in the simulation (0.57 for 12 cores e.g.). The primary outcomes of this work are twofold: One the one hand, the proposed parallel simulation strategies show a dynamic behavior unaltered by the use of multi-core specific technologies. On the other hand, we analyze issues met in our approach to multi-core simulations.\",\"PeriodicalId\":158978,\"journal\":{\"name\":\"2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISIS.2012.196\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISIS.2012.196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simulation of Biological Neural Microcircuits on Multi-core Systems
Our research focuses on the identification and quantification of the impact that multi-core parallelization strategies have on the stability of the result of spiking neural networks simulations. We investigated Open MP-based implementations of the Spike Response Model and Spike Time-Dependent Plasticity for studying behaviors of biological neurons and synapses. The underlying neural microcircuits have small-world topologies. The simulation strategy is a synchronous one. The software development methodology we follow makes use of systematic unit testing and continuous integration, giving us a way to verify various perturbations of simulation results. We carried out investigations on systems having different multi-core processors. The processing speed (spikes/second) of our simulator scales well with the number of cores, but the parallel efficiency is moderate when all cores of the system are used in the simulation (0.57 for 12 cores e.g.). The primary outcomes of this work are twofold: One the one hand, the proposed parallel simulation strategies show a dynamic behavior unaltered by the use of multi-core specific technologies. On the other hand, we analyze issues met in our approach to multi-core simulations.