{"title":"特定应用的MPSoC互连综合的系统级性能估计","authors":"Po-Kuan Huang, Matin Hashemi, S. Ghiasi","doi":"10.1109/SASP.2008.4570792","DOIUrl":null,"url":null,"abstract":"We present a framework for development of streaming applications as concurrent software modules running on multi-processors system-on-chips (MPSoC). We propose an iterative design space exploration mechanism to customize MPSoC architecture for given applications. Central to the exploration engine is our system-level performance estimation methodology, that both quickly and accurately determine quality of candidate architectures. We implemented a number of streaming applications on candidate architectures that were emulated on an FPGA. Hardware measurements show that our system-level performance estimation method incurs only 15% error in predicting application throughput. More importantly, it always correctly guides design space exploration by achieving 100% fidelity in quality-ranking candidate architectures. Compared to behavioral simulation of compiled code, our system-level estimator runs more than 12 times faster, and requires 7 times less memory.","PeriodicalId":356441,"journal":{"name":"2008 Symposium on Application Specific Processors","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"System-Level Performance Estimation for Application-Specific MPSoC Interconnect Synthesis\",\"authors\":\"Po-Kuan Huang, Matin Hashemi, S. Ghiasi\",\"doi\":\"10.1109/SASP.2008.4570792\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a framework for development of streaming applications as concurrent software modules running on multi-processors system-on-chips (MPSoC). We propose an iterative design space exploration mechanism to customize MPSoC architecture for given applications. Central to the exploration engine is our system-level performance estimation methodology, that both quickly and accurately determine quality of candidate architectures. We implemented a number of streaming applications on candidate architectures that were emulated on an FPGA. Hardware measurements show that our system-level performance estimation method incurs only 15% error in predicting application throughput. More importantly, it always correctly guides design space exploration by achieving 100% fidelity in quality-ranking candidate architectures. Compared to behavioral simulation of compiled code, our system-level estimator runs more than 12 times faster, and requires 7 times less memory.\",\"PeriodicalId\":356441,\"journal\":{\"name\":\"2008 Symposium on Application Specific Processors\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Symposium on Application Specific Processors\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SASP.2008.4570792\",\"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 Symposium on Application Specific Processors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SASP.2008.4570792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
System-Level Performance Estimation for Application-Specific MPSoC Interconnect Synthesis
We present a framework for development of streaming applications as concurrent software modules running on multi-processors system-on-chips (MPSoC). We propose an iterative design space exploration mechanism to customize MPSoC architecture for given applications. Central to the exploration engine is our system-level performance estimation methodology, that both quickly and accurately determine quality of candidate architectures. We implemented a number of streaming applications on candidate architectures that were emulated on an FPGA. Hardware measurements show that our system-level performance estimation method incurs only 15% error in predicting application throughput. More importantly, it always correctly guides design space exploration by achieving 100% fidelity in quality-ranking candidate architectures. Compared to behavioral simulation of compiled code, our system-level estimator runs more than 12 times faster, and requires 7 times less memory.