{"title":"一种用于实现计算电路的空间计算体系结构","authors":"D. Grant, G. Lemieux","doi":"10.1109/MNRC.2008.4683373","DOIUrl":null,"url":null,"abstract":"To accelerate many computational software algorithms, designers are implementing them as computational circuits. These algorithms are diverse and include molecular dynamics, weather simulation, video encoding, and financial modelling. Circuit designers repeatedly synthesize and simulate circuits for debugging and incremental design, but due to the size of computational circuits these steps are slow and waste designer productivity. In this paper we present an architecture and tool flow for rapidly compiling and simulating/executing computational circuits. We use a motion estimation circuit to demonstrate the performance vs. capacity scalability of our architecture, and show that the performance is comparable to an FPGA-based design.","PeriodicalId":247684,"journal":{"name":"2008 1st Microsystems and Nanoelectronics Research Conference","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A spatial computing architecture for implementing computational circuits\",\"authors\":\"D. Grant, G. Lemieux\",\"doi\":\"10.1109/MNRC.2008.4683373\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To accelerate many computational software algorithms, designers are implementing them as computational circuits. These algorithms are diverse and include molecular dynamics, weather simulation, video encoding, and financial modelling. Circuit designers repeatedly synthesize and simulate circuits for debugging and incremental design, but due to the size of computational circuits these steps are slow and waste designer productivity. In this paper we present an architecture and tool flow for rapidly compiling and simulating/executing computational circuits. We use a motion estimation circuit to demonstrate the performance vs. capacity scalability of our architecture, and show that the performance is comparable to an FPGA-based design.\",\"PeriodicalId\":247684,\"journal\":{\"name\":\"2008 1st Microsystems and Nanoelectronics Research Conference\",\"volume\":\"2015 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 1st Microsystems and Nanoelectronics Research Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MNRC.2008.4683373\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 1st Microsystems and Nanoelectronics Research Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MNRC.2008.4683373","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A spatial computing architecture for implementing computational circuits
To accelerate many computational software algorithms, designers are implementing them as computational circuits. These algorithms are diverse and include molecular dynamics, weather simulation, video encoding, and financial modelling. Circuit designers repeatedly synthesize and simulate circuits for debugging and incremental design, but due to the size of computational circuits these steps are slow and waste designer productivity. In this paper we present an architecture and tool flow for rapidly compiling and simulating/executing computational circuits. We use a motion estimation circuit to demonstrate the performance vs. capacity scalability of our architecture, and show that the performance is comparable to an FPGA-based design.