{"title":"gpu加速高带宽雷达质心","authors":"D. Brigada, Maximilian Merfeld, Kara Warner","doi":"10.1109/HPEC55821.2022.9926364","DOIUrl":null,"url":null,"abstract":"Radar signal processing is a computationally inten-sive task, especially for high-bandwidth systems. Traditionally, such systems have relied on the interleaving of processing on multiple nodes of large compute clusters to achieve the necessary throughput. Development in general-purpose GPU computing has led to a massive increase in the computational power available to highly parallel tasks. Most parts of the radar signal processing pipeline are well suited for such a task. This paper describes an algorithm for centroiding, a key part of the search radar pipeline that has not yet been demonstrated on a GPU. With this centroiding algorithm, the entire high-data-rate portion of the processing pipeline can be run on the GPU, yielding a speedup factor of approximately 40. The primary benefit of this approach is a massive reduction in data copying from the GPU to the CPU-a factor of over 1200 in this case-alleviating the main barrier to G PU - based radar processing systems.","PeriodicalId":200071,"journal":{"name":"2022 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GPU-Accelerated High-Bandwidth Radar Centroiding\",\"authors\":\"D. Brigada, Maximilian Merfeld, Kara Warner\",\"doi\":\"10.1109/HPEC55821.2022.9926364\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Radar signal processing is a computationally inten-sive task, especially for high-bandwidth systems. Traditionally, such systems have relied on the interleaving of processing on multiple nodes of large compute clusters to achieve the necessary throughput. Development in general-purpose GPU computing has led to a massive increase in the computational power available to highly parallel tasks. Most parts of the radar signal processing pipeline are well suited for such a task. This paper describes an algorithm for centroiding, a key part of the search radar pipeline that has not yet been demonstrated on a GPU. With this centroiding algorithm, the entire high-data-rate portion of the processing pipeline can be run on the GPU, yielding a speedup factor of approximately 40. The primary benefit of this approach is a massive reduction in data copying from the GPU to the CPU-a factor of over 1200 in this case-alleviating the main barrier to G PU - based radar processing systems.\",\"PeriodicalId\":200071,\"journal\":{\"name\":\"2022 IEEE High Performance Extreme Computing Conference (HPEC)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE High Performance Extreme Computing Conference (HPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPEC55821.2022.9926364\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC55821.2022.9926364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Radar signal processing is a computationally inten-sive task, especially for high-bandwidth systems. Traditionally, such systems have relied on the interleaving of processing on multiple nodes of large compute clusters to achieve the necessary throughput. Development in general-purpose GPU computing has led to a massive increase in the computational power available to highly parallel tasks. Most parts of the radar signal processing pipeline are well suited for such a task. This paper describes an algorithm for centroiding, a key part of the search radar pipeline that has not yet been demonstrated on a GPU. With this centroiding algorithm, the entire high-data-rate portion of the processing pipeline can be run on the GPU, yielding a speedup factor of approximately 40. The primary benefit of this approach is a massive reduction in data copying from the GPU to the CPU-a factor of over 1200 in this case-alleviating the main barrier to G PU - based radar processing systems.