Hans Giesen, Raphael Rubin, Benjamin Gojman, A. DeHon
{"title":"特定组件映射中的质量时间权衡:如何训练具有惊人网络延迟的动态可重构门阵列","authors":"Hans Giesen, Raphael Rubin, Benjamin Gojman, A. DeHon","doi":"10.1145/3020078.3026124","DOIUrl":null,"url":null,"abstract":"How should we perform component-specific adaptation for FPGAs? Prior work has demonstrated that the negative effects of variation can be largely mitigated using complete knowledge of device characteristics and full per-FPGA CAD flow. However, the cost of per-FPGA characterization and mapping could be prohibitively expensive. We explore light-weight options for per-FPGA mapping that avoid the need for a priori device characterization and perform less expensive per FPGA customization work. We characterize the tradeoff between Quality-of-Results (energy, delay) and per-device mapping costs for 7 design points ranging from complete mapping based on knowledge to no per-device mapping. We show that it is possible to get 48-77% of the component-specific mapping delay benefit or 57% of the energy benefit with a mapping that takes less than 20 seconds per FPGA. An incremental solution can start execution after a 21 ms bitstream load and converge to 77% delay benefit after 18 seconds of runtime.","PeriodicalId":252039,"journal":{"name":"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Quality-Time Tradeoffs in Component-Specific Mapping: How to Train Your Dynamically Reconfigurable Array of Gates with Outrageous Network-delays\",\"authors\":\"Hans Giesen, Raphael Rubin, Benjamin Gojman, A. DeHon\",\"doi\":\"10.1145/3020078.3026124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"How should we perform component-specific adaptation for FPGAs? Prior work has demonstrated that the negative effects of variation can be largely mitigated using complete knowledge of device characteristics and full per-FPGA CAD flow. However, the cost of per-FPGA characterization and mapping could be prohibitively expensive. We explore light-weight options for per-FPGA mapping that avoid the need for a priori device characterization and perform less expensive per FPGA customization work. We characterize the tradeoff between Quality-of-Results (energy, delay) and per-device mapping costs for 7 design points ranging from complete mapping based on knowledge to no per-device mapping. We show that it is possible to get 48-77% of the component-specific mapping delay benefit or 57% of the energy benefit with a mapping that takes less than 20 seconds per FPGA. An incremental solution can start execution after a 21 ms bitstream load and converge to 77% delay benefit after 18 seconds of runtime.\",\"PeriodicalId\":252039,\"journal\":{\"name\":\"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3020078.3026124\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3020078.3026124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quality-Time Tradeoffs in Component-Specific Mapping: How to Train Your Dynamically Reconfigurable Array of Gates with Outrageous Network-delays
How should we perform component-specific adaptation for FPGAs? Prior work has demonstrated that the negative effects of variation can be largely mitigated using complete knowledge of device characteristics and full per-FPGA CAD flow. However, the cost of per-FPGA characterization and mapping could be prohibitively expensive. We explore light-weight options for per-FPGA mapping that avoid the need for a priori device characterization and perform less expensive per FPGA customization work. We characterize the tradeoff between Quality-of-Results (energy, delay) and per-device mapping costs for 7 design points ranging from complete mapping based on knowledge to no per-device mapping. We show that it is possible to get 48-77% of the component-specific mapping delay benefit or 57% of the energy benefit with a mapping that takes less than 20 seconds per FPGA. An incremental solution can start execution after a 21 ms bitstream load and converge to 77% delay benefit after 18 seconds of runtime.