{"title":"基于GPU平台的RF-PSS分析结构化并行周期Arnoldi射击算法","authors":"Xuexin Liu, Hao Yu, Jacob Relles, S. Tan","doi":"10.1109/ASPDAC.2011.5722172","DOIUrl":null,"url":null,"abstract":"The recent multi/many-core CPUs or GPUs have provided an ideal parallel computing platform to accelerate the time-consuming analysis of radio-frequency/millimeter-wave (RF/ MM) integrated circuit (IC). This paper develops a structured shooting algorithm that can fully take advantage of parallelism in periodic steady state (PSS) analysis. Utilizing periodic structure of the state matrix of RF/ MM-IC simulation, a cyclic-block-structured shooting-Newton method has been parallelized and mapped onto recent GPU platforms. We first present the formulation of the parallel cyclic-block-structured shooting-Newton algorithm, called periodic Arnoldi shooting method. Then we will present its parallel implementation details on GPU. Results from several industrial examples show that the structured parallel shooting-Newton method on Tesla's GPU can lead to speedups of more than 20× compared to the state-of-the-art implicit GMRES methods under the same accuracy on the CPU.","PeriodicalId":316253,"journal":{"name":"16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A structured parallel periodic Arnoldi shooting algorithm for RF-PSS analysis based on GPU platforms\",\"authors\":\"Xuexin Liu, Hao Yu, Jacob Relles, S. Tan\",\"doi\":\"10.1109/ASPDAC.2011.5722172\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recent multi/many-core CPUs or GPUs have provided an ideal parallel computing platform to accelerate the time-consuming analysis of radio-frequency/millimeter-wave (RF/ MM) integrated circuit (IC). This paper develops a structured shooting algorithm that can fully take advantage of parallelism in periodic steady state (PSS) analysis. Utilizing periodic structure of the state matrix of RF/ MM-IC simulation, a cyclic-block-structured shooting-Newton method has been parallelized and mapped onto recent GPU platforms. We first present the formulation of the parallel cyclic-block-structured shooting-Newton algorithm, called periodic Arnoldi shooting method. Then we will present its parallel implementation details on GPU. Results from several industrial examples show that the structured parallel shooting-Newton method on Tesla's GPU can lead to speedups of more than 20× compared to the state-of-the-art implicit GMRES methods under the same accuracy on the CPU.\",\"PeriodicalId\":316253,\"journal\":{\"name\":\"16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-01-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASPDAC.2011.5722172\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPDAC.2011.5722172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A structured parallel periodic Arnoldi shooting algorithm for RF-PSS analysis based on GPU platforms
The recent multi/many-core CPUs or GPUs have provided an ideal parallel computing platform to accelerate the time-consuming analysis of radio-frequency/millimeter-wave (RF/ MM) integrated circuit (IC). This paper develops a structured shooting algorithm that can fully take advantage of parallelism in periodic steady state (PSS) analysis. Utilizing periodic structure of the state matrix of RF/ MM-IC simulation, a cyclic-block-structured shooting-Newton method has been parallelized and mapped onto recent GPU platforms. We first present the formulation of the parallel cyclic-block-structured shooting-Newton algorithm, called periodic Arnoldi shooting method. Then we will present its parallel implementation details on GPU. Results from several industrial examples show that the structured parallel shooting-Newton method on Tesla's GPU can lead to speedups of more than 20× compared to the state-of-the-art implicit GMRES methods under the same accuracy on the CPU.
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