{"title":"在可重构体系结构的多处理范式中调度时间分区","authors":"A. Popp, Y. Moullec, P. Koch","doi":"10.1109/AHS.2009.43","DOIUrl":null,"url":null,"abstract":"In this paper we describe a mapping methodology for heterogeneous reconfigurable architectures consisting of one or more SW processors and one or more reconfigurable units, FPGAs. The mapping methodology consists of a separated track for a) the generation of the configurations for the FPGA by level-based and clustering-based temporal partitioning, and b) the scheduling of those configurations as well as the software tasks, based on two multiprocessor scheduling algorithms: a simple list-based scheduler and the more complex extended dynamic level scheduling algorithm. The mapping methodology is benchmarked by means of randomly created task graphs on an architecture of one SW processor and one FPGA. The results are compared to a 0-1 integer linear programming solution in terms of exploration time as well as the finish-time of all tasks of the application. The results show that, in 90% of the investigated cases, the combination of level-based temporal partitioning and extended dynamic level scheduling gives the best performance in terms of finish-time of the full task-set.","PeriodicalId":318989,"journal":{"name":"2009 NASA/ESA Conference on Adaptive Hardware and Systems","volume":"2002 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Scheduling Temporal Partitions in a Multiprocessing Paradigm for Reconfigurable Architectures\",\"authors\":\"A. Popp, Y. Moullec, P. Koch\",\"doi\":\"10.1109/AHS.2009.43\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we describe a mapping methodology for heterogeneous reconfigurable architectures consisting of one or more SW processors and one or more reconfigurable units, FPGAs. The mapping methodology consists of a separated track for a) the generation of the configurations for the FPGA by level-based and clustering-based temporal partitioning, and b) the scheduling of those configurations as well as the software tasks, based on two multiprocessor scheduling algorithms: a simple list-based scheduler and the more complex extended dynamic level scheduling algorithm. The mapping methodology is benchmarked by means of randomly created task graphs on an architecture of one SW processor and one FPGA. The results are compared to a 0-1 integer linear programming solution in terms of exploration time as well as the finish-time of all tasks of the application. The results show that, in 90% of the investigated cases, the combination of level-based temporal partitioning and extended dynamic level scheduling gives the best performance in terms of finish-time of the full task-set.\",\"PeriodicalId\":318989,\"journal\":{\"name\":\"2009 NASA/ESA Conference on Adaptive Hardware and Systems\",\"volume\":\"2002 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 NASA/ESA Conference on Adaptive Hardware and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AHS.2009.43\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 NASA/ESA Conference on Adaptive Hardware and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AHS.2009.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scheduling Temporal Partitions in a Multiprocessing Paradigm for Reconfigurable Architectures
In this paper we describe a mapping methodology for heterogeneous reconfigurable architectures consisting of one or more SW processors and one or more reconfigurable units, FPGAs. The mapping methodology consists of a separated track for a) the generation of the configurations for the FPGA by level-based and clustering-based temporal partitioning, and b) the scheduling of those configurations as well as the software tasks, based on two multiprocessor scheduling algorithms: a simple list-based scheduler and the more complex extended dynamic level scheduling algorithm. The mapping methodology is benchmarked by means of randomly created task graphs on an architecture of one SW processor and one FPGA. The results are compared to a 0-1 integer linear programming solution in terms of exploration time as well as the finish-time of all tasks of the application. The results show that, in 90% of the investigated cases, the combination of level-based temporal partitioning and extended dynamic level scheduling gives the best performance in terms of finish-time of the full task-set.