{"title":"面向新兴多核心系统的系统真实的片上网络流量建模与生成技术","authors":"Weichen Liu;Zhe Wang;Peng Yang;Jiang Xu;Bin Li;Ravi Lyer;Ramesh Illikkal","doi":"10.1109/TMSCS.2017.2768362","DOIUrl":null,"url":null,"abstract":"As programs for microprocessor architectures, network-on-chip (NoC) traffic patterns are essential tools for NoC performance assessment and design exploration. The fidelity of NoC traffic patterns has profound influence on NoC studies. In this paper, we present a systematic traffic modeling and generation methodology and a traffic suite for efficient evaluation of NoC-based many-core systems. The publicly released MCSL (multi-constraint system-level) traffic suite includes a set of realistic traffic patterns for real-world applications and covers popular NoC architectures. It captures both the communication behaviors in NoCs and the temporal dependencies among them. The MCSL traffic suite can be easily incorporated into existing NoC simulators and significantly improve NoC simulation accuracy. The proposed methodology uses formal computational models to capture both communication and computation requirements of applications. It optimizes application memory requirements, mapping, and scheduling to maximize overall system performance and utilization before extracting traffic patterns through cycle level simulations. Experiment results show that the MCSL traffic suite can be used to study NoC characteristics more accurately than traditional random traffic patterns.","PeriodicalId":100643,"journal":{"name":"IEEE Transactions on Multi-Scale Computing Systems","volume":"4 2","pages":"113-126"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TMSCS.2017.2768362","citationCount":"6","resultStr":"{\"title\":\"A Systematic and Realistic Network-on-Chip Traffic Modeling and Generation Technique for Emerging Many-Core Systems\",\"authors\":\"Weichen Liu;Zhe Wang;Peng Yang;Jiang Xu;Bin Li;Ravi Lyer;Ramesh Illikkal\",\"doi\":\"10.1109/TMSCS.2017.2768362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As programs for microprocessor architectures, network-on-chip (NoC) traffic patterns are essential tools for NoC performance assessment and design exploration. The fidelity of NoC traffic patterns has profound influence on NoC studies. In this paper, we present a systematic traffic modeling and generation methodology and a traffic suite for efficient evaluation of NoC-based many-core systems. The publicly released MCSL (multi-constraint system-level) traffic suite includes a set of realistic traffic patterns for real-world applications and covers popular NoC architectures. It captures both the communication behaviors in NoCs and the temporal dependencies among them. The MCSL traffic suite can be easily incorporated into existing NoC simulators and significantly improve NoC simulation accuracy. The proposed methodology uses formal computational models to capture both communication and computation requirements of applications. It optimizes application memory requirements, mapping, and scheduling to maximize overall system performance and utilization before extracting traffic patterns through cycle level simulations. Experiment results show that the MCSL traffic suite can be used to study NoC characteristics more accurately than traditional random traffic patterns.\",\"PeriodicalId\":100643,\"journal\":{\"name\":\"IEEE Transactions on Multi-Scale Computing Systems\",\"volume\":\"4 2\",\"pages\":\"113-126\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TMSCS.2017.2768362\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Multi-Scale Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/8094019/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Multi-Scale Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/8094019/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Systematic and Realistic Network-on-Chip Traffic Modeling and Generation Technique for Emerging Many-Core Systems
As programs for microprocessor architectures, network-on-chip (NoC) traffic patterns are essential tools for NoC performance assessment and design exploration. The fidelity of NoC traffic patterns has profound influence on NoC studies. In this paper, we present a systematic traffic modeling and generation methodology and a traffic suite for efficient evaluation of NoC-based many-core systems. The publicly released MCSL (multi-constraint system-level) traffic suite includes a set of realistic traffic patterns for real-world applications and covers popular NoC architectures. It captures both the communication behaviors in NoCs and the temporal dependencies among them. The MCSL traffic suite can be easily incorporated into existing NoC simulators and significantly improve NoC simulation accuracy. The proposed methodology uses formal computational models to capture both communication and computation requirements of applications. It optimizes application memory requirements, mapping, and scheduling to maximize overall system performance and utilization before extracting traffic patterns through cycle level simulations. Experiment results show that the MCSL traffic suite can be used to study NoC characteristics more accurately than traditional random traffic patterns.