Tiansheng Zhang, José L. Abellán, A. Joshi, A. Coskun
{"title":"硅光子网络多核系统的热管理","authors":"Tiansheng Zhang, José L. Abellán, A. Joshi, A. Coskun","doi":"10.7873/DATE.2014.320","DOIUrl":null,"url":null,"abstract":"Silicon-photonic network-on-chips (NoCs) provide high bandwidth density; therefore, they are promising candidates to replace electrical NoCs in manycore systems. The silicon-photonic NoCs, however, are sensitive to the temperature gradients that typically occur on the chip, and hence, require proactive thermal management. This paper first provides a design space exploration of silicon-photonic networks in manycore systems and quantifies the performance impact of the temperature gradients for various network bandwidths. The paper then introduces a novel job allocation technique that minimizes the temperature gradients among the ring modulators/filters to improve the application performance. Experimental results for a single-chip 256-core system demonstrate that our policy is able to maintain the maximum network bandwidth. Compared to existing workload allocation policies, the proposed policy improves system performance by up to 26.1% when running a single application and 18.3% for multi-program scenarios.","PeriodicalId":6550,"journal":{"name":"2014 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"42","resultStr":"{\"title\":\"Thermal management of manycore systems with silicon-photonic networks\",\"authors\":\"Tiansheng Zhang, José L. Abellán, A. Joshi, A. Coskun\",\"doi\":\"10.7873/DATE.2014.320\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Silicon-photonic network-on-chips (NoCs) provide high bandwidth density; therefore, they are promising candidates to replace electrical NoCs in manycore systems. The silicon-photonic NoCs, however, are sensitive to the temperature gradients that typically occur on the chip, and hence, require proactive thermal management. This paper first provides a design space exploration of silicon-photonic networks in manycore systems and quantifies the performance impact of the temperature gradients for various network bandwidths. The paper then introduces a novel job allocation technique that minimizes the temperature gradients among the ring modulators/filters to improve the application performance. Experimental results for a single-chip 256-core system demonstrate that our policy is able to maintain the maximum network bandwidth. Compared to existing workload allocation policies, the proposed policy improves system performance by up to 26.1% when running a single application and 18.3% for multi-program scenarios.\",\"PeriodicalId\":6550,\"journal\":{\"name\":\"2014 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"volume\":\"1 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"42\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7873/DATE.2014.320\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7873/DATE.2014.320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thermal management of manycore systems with silicon-photonic networks
Silicon-photonic network-on-chips (NoCs) provide high bandwidth density; therefore, they are promising candidates to replace electrical NoCs in manycore systems. The silicon-photonic NoCs, however, are sensitive to the temperature gradients that typically occur on the chip, and hence, require proactive thermal management. This paper first provides a design space exploration of silicon-photonic networks in manycore systems and quantifies the performance impact of the temperature gradients for various network bandwidths. The paper then introduces a novel job allocation technique that minimizes the temperature gradients among the ring modulators/filters to improve the application performance. Experimental results for a single-chip 256-core system demonstrate that our policy is able to maintain the maximum network bandwidth. Compared to existing workload allocation policies, the proposed policy improves system performance by up to 26.1% when running a single application and 18.3% for multi-program scenarios.