{"title":"用于神经微电路定制构建的FPGA仿真引擎。","authors":"Hugh T Blair, Jason Cong, Di Wu","doi":"10.1109/FCCM.2013.22","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper we describe an FPGA-based platform for high-performance and low-power simulation of neural microcircuits composed from integrate-and-fire (IAF) neurons. Based on high-level synthesis, our platform uses design templates to map hierarchies of neuron model to logic fabrics. This approach bypasses high design complexity and enables easy optimization and design space exploration. We demonstrate the benefits of our platform by simulating a variety of neural microcircuits that perform <i>oscillatory path integration</i>, which evidence suggests may be a critical building block of the navigation system inside a rodent's brain. Experiments show that our FPGA simulation engine for oscillatory neural microcircuits can achieve up to 39× speedup compared to software benchmarks on commodity CPU, and 232× energy reduction compared to embedded ARM core.</p>","PeriodicalId":90518,"journal":{"name":"ICCAD. IEEE/ACM International Conference on Computer-Aided Design","volume":"2013 ","pages":"229"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/FCCM.2013.22","citationCount":"4","resultStr":"{\"title\":\"FPGA Simulation Engine for Customized Construction of Neural Microcircuits.\",\"authors\":\"Hugh T Blair, Jason Cong, Di Wu\",\"doi\":\"10.1109/FCCM.2013.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this paper we describe an FPGA-based platform for high-performance and low-power simulation of neural microcircuits composed from integrate-and-fire (IAF) neurons. Based on high-level synthesis, our platform uses design templates to map hierarchies of neuron model to logic fabrics. This approach bypasses high design complexity and enables easy optimization and design space exploration. We demonstrate the benefits of our platform by simulating a variety of neural microcircuits that perform <i>oscillatory path integration</i>, which evidence suggests may be a critical building block of the navigation system inside a rodent's brain. Experiments show that our FPGA simulation engine for oscillatory neural microcircuits can achieve up to 39× speedup compared to software benchmarks on commodity CPU, and 232× energy reduction compared to embedded ARM core.</p>\",\"PeriodicalId\":90518,\"journal\":{\"name\":\"ICCAD. IEEE/ACM International Conference on Computer-Aided Design\",\"volume\":\"2013 \",\"pages\":\"229\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/FCCM.2013.22\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICCAD. IEEE/ACM International Conference on Computer-Aided Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FCCM.2013.22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICCAD. IEEE/ACM International Conference on Computer-Aided Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCCM.2013.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FPGA Simulation Engine for Customized Construction of Neural Microcircuits.
In this paper we describe an FPGA-based platform for high-performance and low-power simulation of neural microcircuits composed from integrate-and-fire (IAF) neurons. Based on high-level synthesis, our platform uses design templates to map hierarchies of neuron model to logic fabrics. This approach bypasses high design complexity and enables easy optimization and design space exploration. We demonstrate the benefits of our platform by simulating a variety of neural microcircuits that perform oscillatory path integration, which evidence suggests may be a critical building block of the navigation system inside a rodent's brain. Experiments show that our FPGA simulation engine for oscillatory neural microcircuits can achieve up to 39× speedup compared to software benchmarks on commodity CPU, and 232× energy reduction compared to embedded ARM core.