Peng Yang, Zhehui Wang, Zhifei Wang, Xuanqi Chen, Luan H. K. Duong, Jiang Xu
{"title":"硅光子学使机架级多核系统成为可能","authors":"Peng Yang, Zhehui Wang, Zhifei Wang, Xuanqi Chen, Luan H. K. Duong, Jiang Xu","doi":"10.1049/pbpc022e_ch18","DOIUrl":null,"url":null,"abstract":"The increasingly higher demands on computing power from scientific computations, big data processing and deep learning are pushing the emergence of exascale computing systems. Tens of thousands of or even more manycore nodes are connected to build such systems. It imposes huge performance and power challenges on different aspects of the systems. As a basic block in high-performance computing systems, modularized rack will play a significant role in addressing these challenges. In this chapter, we introduce rack-scale optical networks (RSON), a silicon photonics enabled inter/intra-chip network for rack-scale many-core systems. RSON leverages the fact that most traffic is within rack and the high bandwidth and low-latency rack-scale optical network can improve both performance and energy efficiency. We codesign the intra-chip and inter-chip optical networks together with optical internode interface to provide balanced data access to both local memory and remote note's memory, making the nodes within rack cooperate effectively. The evaluations show that RSON can improve the overall performance and energy efficiency dramatically. Specifically, RSON can deliver as much as 5.4x more performance under the same energy consumption compared to traditional InfiniBand connected rack.","PeriodicalId":254920,"journal":{"name":"Many-Core Computing: Hardware and Software","volume":"146 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Silicon photonics enabled rack-scale many-core systems\",\"authors\":\"Peng Yang, Zhehui Wang, Zhifei Wang, Xuanqi Chen, Luan H. K. Duong, Jiang Xu\",\"doi\":\"10.1049/pbpc022e_ch18\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasingly higher demands on computing power from scientific computations, big data processing and deep learning are pushing the emergence of exascale computing systems. Tens of thousands of or even more manycore nodes are connected to build such systems. It imposes huge performance and power challenges on different aspects of the systems. As a basic block in high-performance computing systems, modularized rack will play a significant role in addressing these challenges. In this chapter, we introduce rack-scale optical networks (RSON), a silicon photonics enabled inter/intra-chip network for rack-scale many-core systems. RSON leverages the fact that most traffic is within rack and the high bandwidth and low-latency rack-scale optical network can improve both performance and energy efficiency. We codesign the intra-chip and inter-chip optical networks together with optical internode interface to provide balanced data access to both local memory and remote note's memory, making the nodes within rack cooperate effectively. The evaluations show that RSON can improve the overall performance and energy efficiency dramatically. Specifically, RSON can deliver as much as 5.4x more performance under the same energy consumption compared to traditional InfiniBand connected rack.\",\"PeriodicalId\":254920,\"journal\":{\"name\":\"Many-Core Computing: Hardware and Software\",\"volume\":\"146 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Many-Core Computing: Hardware and Software\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/pbpc022e_ch18\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Many-Core Computing: Hardware and Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/pbpc022e_ch18","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Silicon photonics enabled rack-scale many-core systems
The increasingly higher demands on computing power from scientific computations, big data processing and deep learning are pushing the emergence of exascale computing systems. Tens of thousands of or even more manycore nodes are connected to build such systems. It imposes huge performance and power challenges on different aspects of the systems. As a basic block in high-performance computing systems, modularized rack will play a significant role in addressing these challenges. In this chapter, we introduce rack-scale optical networks (RSON), a silicon photonics enabled inter/intra-chip network for rack-scale many-core systems. RSON leverages the fact that most traffic is within rack and the high bandwidth and low-latency rack-scale optical network can improve both performance and energy efficiency. We codesign the intra-chip and inter-chip optical networks together with optical internode interface to provide balanced data access to both local memory and remote note's memory, making the nodes within rack cooperate effectively. The evaluations show that RSON can improve the overall performance and energy efficiency dramatically. Specifically, RSON can deliver as much as 5.4x more performance under the same energy consumption compared to traditional InfiniBand connected rack.