{"title":"在fpga上实现高吞吐量和带宽效率计算的细粒度数据集成","authors":"Jiyuan Liu , Baoping Wang , Yongming Tang , He Li","doi":"10.1016/j.vlsi.2025.102563","DOIUrl":null,"url":null,"abstract":"<div><div>The surge in terabit-scale computational workloads in AI, smart grids, and scientific computing exacerbates bandwidth bottlenecks in high-performance computing (HPC) infrastructures. Existing solutions have focused on computational architecture optimizations or hardware upgrades, neglecting inefficiencies in data distribution patterns during bus transfers. To solve these issues with maintaining data integrity and bus alignment, we propose a fine-grained data integration (FDI) accelerator on FPGAs based on the proposed adaptive window selection method and data integration algorithm. Evaluated on exemplary HPC workloads, FDI achieves up to 43.8% bandwidth improvements without computational architectural modifications while maintaining at least 22.0% optimizations for data transfer across diverse data streams without altering existing bus protocols or architectures.</div></div>","PeriodicalId":54973,"journal":{"name":"Integration-The Vlsi Journal","volume":"106 ","pages":"Article 102563"},"PeriodicalIF":2.5000,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fine-grained data integration for high throughput and bandwidth-efficient computation on FPGAs\",\"authors\":\"Jiyuan Liu , Baoping Wang , Yongming Tang , He Li\",\"doi\":\"10.1016/j.vlsi.2025.102563\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The surge in terabit-scale computational workloads in AI, smart grids, and scientific computing exacerbates bandwidth bottlenecks in high-performance computing (HPC) infrastructures. Existing solutions have focused on computational architecture optimizations or hardware upgrades, neglecting inefficiencies in data distribution patterns during bus transfers. To solve these issues with maintaining data integrity and bus alignment, we propose a fine-grained data integration (FDI) accelerator on FPGAs based on the proposed adaptive window selection method and data integration algorithm. Evaluated on exemplary HPC workloads, FDI achieves up to 43.8% bandwidth improvements without computational architectural modifications while maintaining at least 22.0% optimizations for data transfer across diverse data streams without altering existing bus protocols or architectures.</div></div>\",\"PeriodicalId\":54973,\"journal\":{\"name\":\"Integration-The Vlsi Journal\",\"volume\":\"106 \",\"pages\":\"Article 102563\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Integration-The Vlsi Journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167926025002202\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integration-The Vlsi Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167926025002202","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Fine-grained data integration for high throughput and bandwidth-efficient computation on FPGAs
The surge in terabit-scale computational workloads in AI, smart grids, and scientific computing exacerbates bandwidth bottlenecks in high-performance computing (HPC) infrastructures. Existing solutions have focused on computational architecture optimizations or hardware upgrades, neglecting inefficiencies in data distribution patterns during bus transfers. To solve these issues with maintaining data integrity and bus alignment, we propose a fine-grained data integration (FDI) accelerator on FPGAs based on the proposed adaptive window selection method and data integration algorithm. Evaluated on exemplary HPC workloads, FDI achieves up to 43.8% bandwidth improvements without computational architectural modifications while maintaining at least 22.0% optimizations for data transfer across diverse data streams without altering existing bus protocols or architectures.
期刊介绍:
Integration''s aim is to cover every aspect of the VLSI area, with an emphasis on cross-fertilization between various fields of science, and the design, verification, test and applications of integrated circuits and systems, as well as closely related topics in process and device technologies. Individual issues will feature peer-reviewed tutorials and articles as well as reviews of recent publications. The intended coverage of the journal can be assessed by examining the following (non-exclusive) list of topics:
Specification methods and languages; Analog/Digital Integrated Circuits and Systems; VLSI architectures; Algorithms, methods and tools for modeling, simulation, synthesis and verification of integrated circuits and systems of any complexity; Embedded systems; High-level synthesis for VLSI systems; Logic synthesis and finite automata; Testing, design-for-test and test generation algorithms; Physical design; Formal verification; Algorithms implemented in VLSI systems; Systems engineering; Heterogeneous systems.