{"title":"射电天文信号处理算法的加速器结构比较","authors":"J. Romein","doi":"10.1109/ICPP.2016.62","DOIUrl":null,"url":null,"abstract":"In this paper, we compare a wide range of accelerator architectures (GPUs from AMD and NVIDIA, the Xeon Phi, and a DSP), by means of a signal-processing pipeline that processes radio-telescope data. We discuss the mapping of the algorithms from this pipeline to the accelerators, and analyze performance. We also analyze energy efficiency, using custom-built, microcontroller-based power sensors that measure the instantaneous power consumption of the accelerators, at millisecond time scale. We show that the GPUs are the fastest and most energy efficient accelerators, and that the differences in performance and energy efficiency are large.","PeriodicalId":409991,"journal":{"name":"2016 45th International Conference on Parallel Processing (ICPP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A Comparison of Accelerator Architectures for Radio-Astronomical Signal-Processing Algorithms\",\"authors\":\"J. Romein\",\"doi\":\"10.1109/ICPP.2016.62\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we compare a wide range of accelerator architectures (GPUs from AMD and NVIDIA, the Xeon Phi, and a DSP), by means of a signal-processing pipeline that processes radio-telescope data. We discuss the mapping of the algorithms from this pipeline to the accelerators, and analyze performance. We also analyze energy efficiency, using custom-built, microcontroller-based power sensors that measure the instantaneous power consumption of the accelerators, at millisecond time scale. We show that the GPUs are the fastest and most energy efficient accelerators, and that the differences in performance and energy efficiency are large.\",\"PeriodicalId\":409991,\"journal\":{\"name\":\"2016 45th International Conference on Parallel Processing (ICPP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 45th International Conference on Parallel Processing (ICPP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPP.2016.62\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 45th International Conference on Parallel Processing (ICPP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPP.2016.62","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Comparison of Accelerator Architectures for Radio-Astronomical Signal-Processing Algorithms
In this paper, we compare a wide range of accelerator architectures (GPUs from AMD and NVIDIA, the Xeon Phi, and a DSP), by means of a signal-processing pipeline that processes radio-telescope data. We discuss the mapping of the algorithms from this pipeline to the accelerators, and analyze performance. We also analyze energy efficiency, using custom-built, microcontroller-based power sensors that measure the instantaneous power consumption of the accelerators, at millisecond time scale. We show that the GPUs are the fastest and most energy efficient accelerators, and that the differences in performance and energy efficiency are large.