{"title":"集成cpu - gpu的系统级平面感知分析","authors":"V. Nandakumar, M. Marek-Sadowska","doi":"10.1145/2593069.2593225","DOIUrl":null,"url":null,"abstract":"Conventional, pre-RTL SoC architectural design space exploration does not account for the chip's floorplan. However, the power and performance of integrated CPU-GPUs are highly dependent not only on architectural specifications and workload characteristics but also on the underlying floorplan. We develop a floorplan-aware system-level analysis framework for integrated CPU-GPUs and demonstrate that the overall energy efficiency can be over/under estimated by up to 25% when floorplan is not account-ed for. The floorplan-aware system-level exploration tool allows us to observe interesting dependencies between architectural choices and physical design. These observations guide the frame-work in determining energy efficient floorplans for wide-range of workloads.","PeriodicalId":433816,"journal":{"name":"2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"System-level floorplan-aware analysis of integrated CPU-GPUs\",\"authors\":\"V. Nandakumar, M. Marek-Sadowska\",\"doi\":\"10.1145/2593069.2593225\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Conventional, pre-RTL SoC architectural design space exploration does not account for the chip's floorplan. However, the power and performance of integrated CPU-GPUs are highly dependent not only on architectural specifications and workload characteristics but also on the underlying floorplan. We develop a floorplan-aware system-level analysis framework for integrated CPU-GPUs and demonstrate that the overall energy efficiency can be over/under estimated by up to 25% when floorplan is not account-ed for. The floorplan-aware system-level exploration tool allows us to observe interesting dependencies between architectural choices and physical design. These observations guide the frame-work in determining energy efficient floorplans for wide-range of workloads.\",\"PeriodicalId\":433816,\"journal\":{\"name\":\"2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2593069.2593225\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2593069.2593225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
System-level floorplan-aware analysis of integrated CPU-GPUs
Conventional, pre-RTL SoC architectural design space exploration does not account for the chip's floorplan. However, the power and performance of integrated CPU-GPUs are highly dependent not only on architectural specifications and workload characteristics but also on the underlying floorplan. We develop a floorplan-aware system-level analysis framework for integrated CPU-GPUs and demonstrate that the overall energy efficiency can be over/under estimated by up to 25% when floorplan is not account-ed for. The floorplan-aware system-level exploration tool allows us to observe interesting dependencies between architectural choices and physical design. These observations guide the frame-work in determining energy efficient floorplans for wide-range of workloads.