{"title":"MORP:具有嵌入式可重构结构的处理器的最大寿命优化","authors":"Artjom Grudnitsky, L. Bauer, J. Henkel","doi":"10.1145/2554688.2554782","DOIUrl":null,"url":null,"abstract":"Processors with an embedded runtime reconfigurable fabric have been explored in academia and industry started production of commercial platforms (e.g. Xilinx Zynq-7000). While providing significant performance and efficiency, the comparatively long reconfiguration time limits these advantages when applications request reconfigurations frequently. In multi-tasking systems frequent task switches lead to frequent reconfigurations and thus are a major hurdle for further performance increases. Sophisticated task scheduling is a very effective means to reduce the negative impact of these reconfiguration requests. In this paper, we propose an online approach for combined task scheduling and re-distribution of reconfigurable fabric between tasks in order to reduce the makespan, i.e. the completion time of a taskset that executes on a runtime reconfigurable processor. Evaluating multiple tasksets comprised of multimedia applications, our proposed approach achieves makespans that are on average only 2.8% worse than those achieved by a theoretical optimal scheduling that assumes zero-overhead reconfiguration time. In comparison, scheduling approaches deployed in state-of-the-art reconfigurable processors achieve makespans 14%-20% worse than optimal. As our approach is a purely software-side mechanism, a multitude of reconfigurable platforms aimed at multi-tasking can benefit from it.","PeriodicalId":390562,"journal":{"name":"Proceedings of the 2014 ACM/SIGDA international symposium on Field-programmable gate arrays","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"MORP: makespan optimization for processors with an embedded reconfigurable fabric\",\"authors\":\"Artjom Grudnitsky, L. Bauer, J. Henkel\",\"doi\":\"10.1145/2554688.2554782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Processors with an embedded runtime reconfigurable fabric have been explored in academia and industry started production of commercial platforms (e.g. Xilinx Zynq-7000). While providing significant performance and efficiency, the comparatively long reconfiguration time limits these advantages when applications request reconfigurations frequently. In multi-tasking systems frequent task switches lead to frequent reconfigurations and thus are a major hurdle for further performance increases. Sophisticated task scheduling is a very effective means to reduce the negative impact of these reconfiguration requests. In this paper, we propose an online approach for combined task scheduling and re-distribution of reconfigurable fabric between tasks in order to reduce the makespan, i.e. the completion time of a taskset that executes on a runtime reconfigurable processor. Evaluating multiple tasksets comprised of multimedia applications, our proposed approach achieves makespans that are on average only 2.8% worse than those achieved by a theoretical optimal scheduling that assumes zero-overhead reconfiguration time. In comparison, scheduling approaches deployed in state-of-the-art reconfigurable processors achieve makespans 14%-20% worse than optimal. As our approach is a purely software-side mechanism, a multitude of reconfigurable platforms aimed at multi-tasking can benefit from it.\",\"PeriodicalId\":390562,\"journal\":{\"name\":\"Proceedings of the 2014 ACM/SIGDA international symposium on Field-programmable gate arrays\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2014 ACM/SIGDA international symposium on Field-programmable gate arrays\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2554688.2554782\",\"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 2014 ACM/SIGDA international symposium on Field-programmable gate arrays","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2554688.2554782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MORP: makespan optimization for processors with an embedded reconfigurable fabric
Processors with an embedded runtime reconfigurable fabric have been explored in academia and industry started production of commercial platforms (e.g. Xilinx Zynq-7000). While providing significant performance and efficiency, the comparatively long reconfiguration time limits these advantages when applications request reconfigurations frequently. In multi-tasking systems frequent task switches lead to frequent reconfigurations and thus are a major hurdle for further performance increases. Sophisticated task scheduling is a very effective means to reduce the negative impact of these reconfiguration requests. In this paper, we propose an online approach for combined task scheduling and re-distribution of reconfigurable fabric between tasks in order to reduce the makespan, i.e. the completion time of a taskset that executes on a runtime reconfigurable processor. Evaluating multiple tasksets comprised of multimedia applications, our proposed approach achieves makespans that are on average only 2.8% worse than those achieved by a theoretical optimal scheduling that assumes zero-overhead reconfiguration time. In comparison, scheduling approaches deployed in state-of-the-art reconfigurable processors achieve makespans 14%-20% worse than optimal. As our approach is a purely software-side mechanism, a multitude of reconfigurable platforms aimed at multi-tasking can benefit from it.