{"title":"基于约束规划的fpga高级编程环境的最优调度","authors":"Pascal Jungblut, D. Kranzlmüller","doi":"10.1109/IPDPSW55747.2022.00025","DOIUrl":null,"url":null,"abstract":"Scheduling tasks on reconfigurable hardware is a well-known problem. Yet, the adoption of advanced scheduling strategies for reconfigurable systems is still low. We argue that a pragmatic solution not relying on low-level features like partial reconfiguration is feasible. Our theoretical framework describes reconfigurable hardware in a simple and abstract way. The constraints of a schedule are used to derive a constraint programming formulation. We present two heuristic algorithms based on list scheduling and on clustering, respectively. The model is evaluated and compared to partial reconfiguration using parameters from a previously observed LU decomposition on an FPGA. The losses are compared to a conventional, optimal approach. It can be integrated into existing technologies to aide the adoption of high-level FPGA programming environments.","PeriodicalId":286968,"journal":{"name":"2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Schedules for High-Level Programming Environments on FPGAs with Constraint Programming\",\"authors\":\"Pascal Jungblut, D. Kranzlmüller\",\"doi\":\"10.1109/IPDPSW55747.2022.00025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Scheduling tasks on reconfigurable hardware is a well-known problem. Yet, the adoption of advanced scheduling strategies for reconfigurable systems is still low. We argue that a pragmatic solution not relying on low-level features like partial reconfiguration is feasible. Our theoretical framework describes reconfigurable hardware in a simple and abstract way. The constraints of a schedule are used to derive a constraint programming formulation. We present two heuristic algorithms based on list scheduling and on clustering, respectively. The model is evaluated and compared to partial reconfiguration using parameters from a previously observed LU decomposition on an FPGA. The losses are compared to a conventional, optimal approach. It can be integrated into existing technologies to aide the adoption of high-level FPGA programming environments.\",\"PeriodicalId\":286968,\"journal\":{\"name\":\"2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPDPSW55747.2022.00025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPSW55747.2022.00025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Schedules for High-Level Programming Environments on FPGAs with Constraint Programming
Scheduling tasks on reconfigurable hardware is a well-known problem. Yet, the adoption of advanced scheduling strategies for reconfigurable systems is still low. We argue that a pragmatic solution not relying on low-level features like partial reconfiguration is feasible. Our theoretical framework describes reconfigurable hardware in a simple and abstract way. The constraints of a schedule are used to derive a constraint programming formulation. We present two heuristic algorithms based on list scheduling and on clustering, respectively. The model is evaluated and compared to partial reconfiguration using parameters from a previously observed LU decomposition on an FPGA. The losses are compared to a conventional, optimal approach. It can be integrated into existing technologies to aide the adoption of high-level FPGA programming environments.