{"title":"有限元电磁学的硬件加速:现场可编程门阵列的高效稀疏矩阵浮点计算","authors":"Y. El Kurdi, W. Gross, D. Giannacopoulos","doi":"10.1109/CEFC-06.2006.1633187","DOIUrl":null,"url":null,"abstract":"Custom hardware acceleration of electromagnetics computations leverages favorable industry trends, which indicate reconfigurable hardware devices such as field programmable gate arrays (FPGAs) may soon outperform general purpose CPUs. We present a new striping method for efficient sparse matrix-vector multiplication implemented in a deeply pipelined FPGA design. The effectiveness of the new method is illustrated for a representative set of finite element matrices","PeriodicalId":262549,"journal":{"name":"2006 12th Biennial IEEE Conference on Electromagnetic Field Computation","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Hardware Acceleration for Finite Element Electromagnetics: Efficient Sparse Matrix Floating-Point Computations with Field Programmable Gate Arrays\",\"authors\":\"Y. El Kurdi, W. Gross, D. Giannacopoulos\",\"doi\":\"10.1109/CEFC-06.2006.1633187\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Custom hardware acceleration of electromagnetics computations leverages favorable industry trends, which indicate reconfigurable hardware devices such as field programmable gate arrays (FPGAs) may soon outperform general purpose CPUs. We present a new striping method for efficient sparse matrix-vector multiplication implemented in a deeply pipelined FPGA design. The effectiveness of the new method is illustrated for a representative set of finite element matrices\",\"PeriodicalId\":262549,\"journal\":{\"name\":\"2006 12th Biennial IEEE Conference on Electromagnetic Field Computation\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 12th Biennial IEEE Conference on Electromagnetic Field Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEFC-06.2006.1633187\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 12th Biennial IEEE Conference on Electromagnetic Field Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEFC-06.2006.1633187","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hardware Acceleration for Finite Element Electromagnetics: Efficient Sparse Matrix Floating-Point Computations with Field Programmable Gate Arrays
Custom hardware acceleration of electromagnetics computations leverages favorable industry trends, which indicate reconfigurable hardware devices such as field programmable gate arrays (FPGAs) may soon outperform general purpose CPUs. We present a new striping method for efficient sparse matrix-vector multiplication implemented in a deeply pipelined FPGA design. The effectiveness of the new method is illustrated for a representative set of finite element matrices