{"title":"图形处理器上的图像域网格划分","authors":"B. Veenboer, M. Petschow, J. Romein","doi":"10.1109/IPDPS.2017.68","DOIUrl":null,"url":null,"abstract":"Realizing the next generation of radio telescopes such as the Square Kilometre Array (SKA) requires both more efficient hardware and algorithms than today's technology provides. The recently introduced image-domain gridding (IDG) algorithm is a novel approach towards solving the most compute-intensive parts of creating sky images: gridding and degridding. It avoids the performance bottlenecks of traditional AW-projection gridding by applying instrumental and environmental corrections in the image domain instead of in the Fourier domain. In this paper, we present the first implementations of this new algorithm for CPUs and Graphics Processing Units (GPUs). A thorough performance analysis, in which we apply a modified roofline analysis, shows that our parallelization approaches and optimizations lead to nearly optimal performance on these architectures. The analysis also indicates that, by leveraging dedicated hardware to evaluate trigonometric functions, GPUs are both much faster and more energy efficient than regular CPUs. This makes IDG on GPUs a candidate for meeting the computational and energy efficiency constraints of future telescopes.","PeriodicalId":209524,"journal":{"name":"2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Image-Domain Gridding on Graphics Processors\",\"authors\":\"B. Veenboer, M. Petschow, J. Romein\",\"doi\":\"10.1109/IPDPS.2017.68\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Realizing the next generation of radio telescopes such as the Square Kilometre Array (SKA) requires both more efficient hardware and algorithms than today's technology provides. The recently introduced image-domain gridding (IDG) algorithm is a novel approach towards solving the most compute-intensive parts of creating sky images: gridding and degridding. It avoids the performance bottlenecks of traditional AW-projection gridding by applying instrumental and environmental corrections in the image domain instead of in the Fourier domain. In this paper, we present the first implementations of this new algorithm for CPUs and Graphics Processing Units (GPUs). A thorough performance analysis, in which we apply a modified roofline analysis, shows that our parallelization approaches and optimizations lead to nearly optimal performance on these architectures. The analysis also indicates that, by leveraging dedicated hardware to evaluate trigonometric functions, GPUs are both much faster and more energy efficient than regular CPUs. This makes IDG on GPUs a candidate for meeting the computational and energy efficiency constraints of future telescopes.\",\"PeriodicalId\":209524,\"journal\":{\"name\":\"2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPDPS.2017.68\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS.2017.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Realizing the next generation of radio telescopes such as the Square Kilometre Array (SKA) requires both more efficient hardware and algorithms than today's technology provides. The recently introduced image-domain gridding (IDG) algorithm is a novel approach towards solving the most compute-intensive parts of creating sky images: gridding and degridding. It avoids the performance bottlenecks of traditional AW-projection gridding by applying instrumental and environmental corrections in the image domain instead of in the Fourier domain. In this paper, we present the first implementations of this new algorithm for CPUs and Graphics Processing Units (GPUs). A thorough performance analysis, in which we apply a modified roofline analysis, shows that our parallelization approaches and optimizations lead to nearly optimal performance on these architectures. The analysis also indicates that, by leveraging dedicated hardware to evaluate trigonometric functions, GPUs are both much faster and more energy efficient than regular CPUs. This makes IDG on GPUs a candidate for meeting the computational and energy efficiency constraints of future telescopes.