{"title":"用于快速、低功耗回路执行的功能单元网络","authors":"Georgios Dimitriou, A. Tziouvaras","doi":"10.1504/ijird.2015.071091","DOIUrl":null,"url":null,"abstract":"Computer architects have focused on advanced processor designs that achieve high performance through multiple cores and multiple threads, and at the same time keep power dissipation low. In this work, we propose a processor back end, specifically designed for rapid loop execution and low power dissipation. This back end consists of a network of functional unit nodes, in which instructions of the loop body are issued only once until loop completion. In this way, we exploit both instruction-level and data-flow parallelism. We attempt to decrease power consumption by turning off the front end and all unused functional units. Simulation results show that the proposed back end can accelerate Livermore loops by up to N/k, for a network of N units and loop body size of N instructions, and an issue rate of k instructions per cycle, when compared to scalar or superscalar RISC execution.","PeriodicalId":260303,"journal":{"name":"International Journal of Innovation and Regional Development","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A functional unit network for rapid, low-power loop execution\",\"authors\":\"Georgios Dimitriou, A. Tziouvaras\",\"doi\":\"10.1504/ijird.2015.071091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computer architects have focused on advanced processor designs that achieve high performance through multiple cores and multiple threads, and at the same time keep power dissipation low. In this work, we propose a processor back end, specifically designed for rapid loop execution and low power dissipation. This back end consists of a network of functional unit nodes, in which instructions of the loop body are issued only once until loop completion. In this way, we exploit both instruction-level and data-flow parallelism. We attempt to decrease power consumption by turning off the front end and all unused functional units. Simulation results show that the proposed back end can accelerate Livermore loops by up to N/k, for a network of N units and loop body size of N instructions, and an issue rate of k instructions per cycle, when compared to scalar or superscalar RISC execution.\",\"PeriodicalId\":260303,\"journal\":{\"name\":\"International Journal of Innovation and Regional Development\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovation and Regional Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijird.2015.071091\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovation and Regional Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijird.2015.071091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A functional unit network for rapid, low-power loop execution
Computer architects have focused on advanced processor designs that achieve high performance through multiple cores and multiple threads, and at the same time keep power dissipation low. In this work, we propose a processor back end, specifically designed for rapid loop execution and low power dissipation. This back end consists of a network of functional unit nodes, in which instructions of the loop body are issued only once until loop completion. In this way, we exploit both instruction-level and data-flow parallelism. We attempt to decrease power consumption by turning off the front end and all unused functional units. Simulation results show that the proposed back end can accelerate Livermore loops by up to N/k, for a network of N units and loop body size of N instructions, and an issue rate of k instructions per cycle, when compared to scalar or superscalar RISC execution.