{"title":"fpga加速全球布局的扩展","authors":"Shounak Dhar, L. Singhal, M. Iyer, D. Pan","doi":"10.1109/HPEC.2019.8916251","DOIUrl":null,"url":null,"abstract":"Placement takes a large part of the runtime in an Electronic Design Automation design implementation flow. In modern industrial and academic physical design impementation tools, global placement consumes a significant part of the overall placement runtime. Many of these global placers decouple the placement problem into two main parts - numerical optimization and spreading. In this paper, we propose a new and massively parallel spreading algorithm and also accelerate a part of this algorithm on FPGA. Our algorithm produces placements with comparable quality when integrated into a state-of-the-art academic placer. We formulate the spreading problem as a system of fluid flows across reservoirs and mathematically prove that this formulation produces flows without cycles when solved as a continuous-time system. We also propose a flow correction algorithm to make the flows monotonic, reduce total cell displacement and remove cycles which may arise during the discretization process. Our new flow correction algorithm has a better time complexity for cycle removal than previous algorithms for finding cycles in a generic graph. When compared to our previously published linear programming based spreading algorithm [1], our new fluid-flow based multi-threaded spreading algorithm is 3.44x faster, and the corresponding FPGA-accelerated version is 5.15x faster.","PeriodicalId":184253,"journal":{"name":"2019 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"FPGA-Accelerated Spreading for Global Placement\",\"authors\":\"Shounak Dhar, L. Singhal, M. Iyer, D. Pan\",\"doi\":\"10.1109/HPEC.2019.8916251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Placement takes a large part of the runtime in an Electronic Design Automation design implementation flow. In modern industrial and academic physical design impementation tools, global placement consumes a significant part of the overall placement runtime. Many of these global placers decouple the placement problem into two main parts - numerical optimization and spreading. In this paper, we propose a new and massively parallel spreading algorithm and also accelerate a part of this algorithm on FPGA. Our algorithm produces placements with comparable quality when integrated into a state-of-the-art academic placer. We formulate the spreading problem as a system of fluid flows across reservoirs and mathematically prove that this formulation produces flows without cycles when solved as a continuous-time system. We also propose a flow correction algorithm to make the flows monotonic, reduce total cell displacement and remove cycles which may arise during the discretization process. Our new flow correction algorithm has a better time complexity for cycle removal than previous algorithms for finding cycles in a generic graph. When compared to our previously published linear programming based spreading algorithm [1], our new fluid-flow based multi-threaded spreading algorithm is 3.44x faster, and the corresponding FPGA-accelerated version is 5.15x faster.\",\"PeriodicalId\":184253,\"journal\":{\"name\":\"2019 IEEE High Performance Extreme Computing Conference (HPEC)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE High Performance Extreme Computing Conference (HPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPEC.2019.8916251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC.2019.8916251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Placement takes a large part of the runtime in an Electronic Design Automation design implementation flow. In modern industrial and academic physical design impementation tools, global placement consumes a significant part of the overall placement runtime. Many of these global placers decouple the placement problem into two main parts - numerical optimization and spreading. In this paper, we propose a new and massively parallel spreading algorithm and also accelerate a part of this algorithm on FPGA. Our algorithm produces placements with comparable quality when integrated into a state-of-the-art academic placer. We formulate the spreading problem as a system of fluid flows across reservoirs and mathematically prove that this formulation produces flows without cycles when solved as a continuous-time system. We also propose a flow correction algorithm to make the flows monotonic, reduce total cell displacement and remove cycles which may arise during the discretization process. Our new flow correction algorithm has a better time complexity for cycle removal than previous algorithms for finding cycles in a generic graph. When compared to our previously published linear programming based spreading algorithm [1], our new fluid-flow based multi-threaded spreading algorithm is 3.44x faster, and the corresponding FPGA-accelerated version is 5.15x faster.