{"title":"高级合成中环路管道的最优绑定和端口分配","authors":"Nicolai Fiege, Patrick Sittel, P. Zipf","doi":"10.1109/FPL57034.2022.00047","DOIUrl":null,"url":null,"abstract":"In order to provide high throughput for custom hardware implementations, academic and commercial high-level synthesis (HLS) tools use loop pipelining by modulo scheduling. When provided a resource allocation and a schedule, the binding algorithm can be used to reduce the number of required lifetime registers (LR) and multiplexers (MUX). Contrary to non-modulo schedules, optimal solutions to the binding problem for implementing modulo schedules with respect to minimizing required LRs and MUXs have not been published. To address this topic, we propose a novel optimal binding algorithm to simultaneously minimize MUX and LR costs for loop pipelining using Integer Linear Programming. We evaluated our algorithm on a set of commonly used benchmark instances from digital signal processing and report that all encountered problems could be solved, with 36.53% of the solutions being optimal within a time limit of only five minutes. Compared to worst case evaluations, we report MUX and LR savings of up to 42.74% and 26.62%, respectively. To evaluate the impact on the resulting circuit after place and route, we studied FPGA implementations of several benchmark instances and recorded look-up table and flip-flop reductions of up to 13.70% and 5.24%, respectively, compared to previous work and to an extensive set of randomly generated bindings when state-of-the-art algorithms fail to find a feasible solution.","PeriodicalId":380116,"journal":{"name":"2022 32nd International Conference on Field-Programmable Logic and Applications (FPL)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimal Binding and Port Assignment for Loop Pipelining in High-Level Synthesis\",\"authors\":\"Nicolai Fiege, Patrick Sittel, P. Zipf\",\"doi\":\"10.1109/FPL57034.2022.00047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to provide high throughput for custom hardware implementations, academic and commercial high-level synthesis (HLS) tools use loop pipelining by modulo scheduling. When provided a resource allocation and a schedule, the binding algorithm can be used to reduce the number of required lifetime registers (LR) and multiplexers (MUX). Contrary to non-modulo schedules, optimal solutions to the binding problem for implementing modulo schedules with respect to minimizing required LRs and MUXs have not been published. To address this topic, we propose a novel optimal binding algorithm to simultaneously minimize MUX and LR costs for loop pipelining using Integer Linear Programming. We evaluated our algorithm on a set of commonly used benchmark instances from digital signal processing and report that all encountered problems could be solved, with 36.53% of the solutions being optimal within a time limit of only five minutes. Compared to worst case evaluations, we report MUX and LR savings of up to 42.74% and 26.62%, respectively. To evaluate the impact on the resulting circuit after place and route, we studied FPGA implementations of several benchmark instances and recorded look-up table and flip-flop reductions of up to 13.70% and 5.24%, respectively, compared to previous work and to an extensive set of randomly generated bindings when state-of-the-art algorithms fail to find a feasible solution.\",\"PeriodicalId\":380116,\"journal\":{\"name\":\"2022 32nd International Conference on Field-Programmable Logic and Applications (FPL)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 32nd International Conference on Field-Programmable Logic and Applications (FPL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FPL57034.2022.00047\",\"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 32nd International Conference on Field-Programmable Logic and Applications (FPL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPL57034.2022.00047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Binding and Port Assignment for Loop Pipelining in High-Level Synthesis
In order to provide high throughput for custom hardware implementations, academic and commercial high-level synthesis (HLS) tools use loop pipelining by modulo scheduling. When provided a resource allocation and a schedule, the binding algorithm can be used to reduce the number of required lifetime registers (LR) and multiplexers (MUX). Contrary to non-modulo schedules, optimal solutions to the binding problem for implementing modulo schedules with respect to minimizing required LRs and MUXs have not been published. To address this topic, we propose a novel optimal binding algorithm to simultaneously minimize MUX and LR costs for loop pipelining using Integer Linear Programming. We evaluated our algorithm on a set of commonly used benchmark instances from digital signal processing and report that all encountered problems could be solved, with 36.53% of the solutions being optimal within a time limit of only five minutes. Compared to worst case evaluations, we report MUX and LR savings of up to 42.74% and 26.62%, respectively. To evaluate the impact on the resulting circuit after place and route, we studied FPGA implementations of several benchmark instances and recorded look-up table and flip-flop reductions of up to 13.70% and 5.24%, respectively, compared to previous work and to an extensive set of randomly generated bindings when state-of-the-art algorithms fail to find a feasible solution.