{"title":"通过可控双元网络加速矢量置换指令的执行","authors":"Shabirahmed Badashasab Jigalur;Daniel Jiménez Mazure;Teresa Cervero Garcia;Yen-Cheng Kuan","doi":"10.1109/LCA.2025.3548527","DOIUrl":null,"url":null,"abstract":"High-performance computing applications rely heavily on vector instructions to accelerate data processing. In this letter, we propose a controllable bitonic network (CBN) and use it as a lane interconnect to efficiently rearrange data across vector lanes of a vector processing unit to accelerate the execution of vector permutation instructions (VPIs). Our work focuses on the RISC-V vector instruction set because of its configurable vector length support. Through simulations with vector-permutation-intensive applications of a RISC-V vector benchmark suite (RiVEC), the proposed approach with an eight-lane 64-bit CBN demonstrates an average speedup of ≥6× regarding the VPI execution time over a conventional ring-network-based approach. In addition, to verify our approach on hardware, we implemented a processor system with an eight-lane 16-bit CBN on an AMD A7-100T FPGA operating at 20 MHz, demonstrating single-cycle execution of the RISC-V <italic>vr.gather</i> and <italic>vr.scatter</i> instructions.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"24 1","pages":"133-136"},"PeriodicalIF":1.4000,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accelerating Vector Permutation Instruction Execution via Controllable Bitonic Network\",\"authors\":\"Shabirahmed Badashasab Jigalur;Daniel Jiménez Mazure;Teresa Cervero Garcia;Yen-Cheng Kuan\",\"doi\":\"10.1109/LCA.2025.3548527\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-performance computing applications rely heavily on vector instructions to accelerate data processing. In this letter, we propose a controllable bitonic network (CBN) and use it as a lane interconnect to efficiently rearrange data across vector lanes of a vector processing unit to accelerate the execution of vector permutation instructions (VPIs). Our work focuses on the RISC-V vector instruction set because of its configurable vector length support. Through simulations with vector-permutation-intensive applications of a RISC-V vector benchmark suite (RiVEC), the proposed approach with an eight-lane 64-bit CBN demonstrates an average speedup of ≥6× regarding the VPI execution time over a conventional ring-network-based approach. In addition, to verify our approach on hardware, we implemented a processor system with an eight-lane 16-bit CBN on an AMD A7-100T FPGA operating at 20 MHz, demonstrating single-cycle execution of the RISC-V <italic>vr.gather</i> and <italic>vr.scatter</i> instructions.\",\"PeriodicalId\":51248,\"journal\":{\"name\":\"IEEE Computer Architecture Letters\",\"volume\":\"24 1\",\"pages\":\"133-136\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2025-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Computer Architecture Letters\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10910116/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Computer Architecture Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10910116/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Accelerating Vector Permutation Instruction Execution via Controllable Bitonic Network
High-performance computing applications rely heavily on vector instructions to accelerate data processing. In this letter, we propose a controllable bitonic network (CBN) and use it as a lane interconnect to efficiently rearrange data across vector lanes of a vector processing unit to accelerate the execution of vector permutation instructions (VPIs). Our work focuses on the RISC-V vector instruction set because of its configurable vector length support. Through simulations with vector-permutation-intensive applications of a RISC-V vector benchmark suite (RiVEC), the proposed approach with an eight-lane 64-bit CBN demonstrates an average speedup of ≥6× regarding the VPI execution time over a conventional ring-network-based approach. In addition, to verify our approach on hardware, we implemented a processor system with an eight-lane 16-bit CBN on an AMD A7-100T FPGA operating at 20 MHz, demonstrating single-cycle execution of the RISC-V vr.gather and vr.scatter instructions.
期刊介绍:
IEEE Computer Architecture Letters is a rigorously peer-reviewed forum for publishing early, high-impact results in the areas of uni- and multiprocessor computer systems, computer architecture, microarchitecture, workload characterization, performance evaluation and simulation techniques, and power-aware computing. Submissions are welcomed on any topic in computer architecture, especially but not limited to: microprocessor and multiprocessor systems, microarchitecture and ILP processors, workload characterization, performance evaluation and simulation techniques, compiler-hardware and operating system-hardware interactions, interconnect architectures, memory and cache systems, power and thermal issues at the architecture level, I/O architectures and techniques, independent validation of previously published results, analysis of unsuccessful techniques, domain-specific processor architectures (e.g., embedded, graphics, network, etc.), real-time and high-availability architectures, reconfigurable systems.