{"title":"使用零抑制二值决策图的CGRA映射","authors":"Rami Beidas, J. Anderson","doi":"10.1109/asp-dac52403.2022.9712571","DOIUrl":null,"url":null,"abstract":"The restricted routing networks of coarse-grained reconfigurable arrays (CGRAs) have motivated CAD developers to utilize exact solutions, such as integer linear programming (ILP), in formu-lating and solving the mapping problem. Such so-lutions that rely on general purpose optimizers have not been shown to scale. In this work, we formu-late CGRA mapping as a solution enumeration and selection problem, relying on the efficiency of zero-suppressed binary decision diagrams (ZDDs) [22] to capture the solution space. For small-to-moderate size problems, it is possible to capture every possible map-ping in a few megabytes. For larger problems, thou-sands if not millions of solutions can be enumerated. The final mapping is a simple linear-time DAG traver-sal of the enumeration ZDD. The proposed solution was implemented in the CGRA-ME [6] framework. A speedup of two orders of magnitude was obtained when compared with past solutions targeting smaller CGRA devices. Larger devices beyond the capacity of those solutions are now accessible.","PeriodicalId":239260,"journal":{"name":"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"CGRA Mapping Using Zero-Suppressed Binary Decision Diagrams\",\"authors\":\"Rami Beidas, J. Anderson\",\"doi\":\"10.1109/asp-dac52403.2022.9712571\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The restricted routing networks of coarse-grained reconfigurable arrays (CGRAs) have motivated CAD developers to utilize exact solutions, such as integer linear programming (ILP), in formu-lating and solving the mapping problem. Such so-lutions that rely on general purpose optimizers have not been shown to scale. In this work, we formu-late CGRA mapping as a solution enumeration and selection problem, relying on the efficiency of zero-suppressed binary decision diagrams (ZDDs) [22] to capture the solution space. For small-to-moderate size problems, it is possible to capture every possible map-ping in a few megabytes. For larger problems, thou-sands if not millions of solutions can be enumerated. The final mapping is a simple linear-time DAG traver-sal of the enumeration ZDD. The proposed solution was implemented in the CGRA-ME [6] framework. A speedup of two orders of magnitude was obtained when compared with past solutions targeting smaller CGRA devices. Larger devices beyond the capacity of those solutions are now accessible.\",\"PeriodicalId\":239260,\"journal\":{\"name\":\"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)\",\"volume\":\"235 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/asp-dac52403.2022.9712571\",\"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 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/asp-dac52403.2022.9712571","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CGRA Mapping Using Zero-Suppressed Binary Decision Diagrams
The restricted routing networks of coarse-grained reconfigurable arrays (CGRAs) have motivated CAD developers to utilize exact solutions, such as integer linear programming (ILP), in formu-lating and solving the mapping problem. Such so-lutions that rely on general purpose optimizers have not been shown to scale. In this work, we formu-late CGRA mapping as a solution enumeration and selection problem, relying on the efficiency of zero-suppressed binary decision diagrams (ZDDs) [22] to capture the solution space. For small-to-moderate size problems, it is possible to capture every possible map-ping in a few megabytes. For larger problems, thou-sands if not millions of solutions can be enumerated. The final mapping is a simple linear-time DAG traver-sal of the enumeration ZDD. The proposed solution was implemented in the CGRA-ME [6] framework. A speedup of two orders of magnitude was obtained when compared with past solutions targeting smaller CGRA devices. Larger devices beyond the capacity of those solutions are now accessible.