{"title":"fpga上无补零稀疏矩阵向量乘法","authors":"Jiasen Huang, Junyan Ren, Wenbo Yin, Lingli Wang","doi":"10.1109/FPT.2014.7082800","DOIUrl":null,"url":null,"abstract":"Sparse Matrix-Vector Multiplication (SpMxV) algorithms suffer heavy performance penalties due to irregular memory accesses. In this paper, we introduce a novel compressed element storage (CES) format, in which the additional data structures for indexing are abandoned, and each location associated with the non-zero element of the matrix is now indicated by the name of a variable multiplied by the corresponding element of the vector. To ensure fastest access and parallel access without data hazards, on-chip registers are used exclusively to replace the BRAM or off-chip DRAM/SRAM to hold all the SpMxV data. On-chip DSP resources are fully utilized so as to ensure a maximum number of multipliers concurrently working.","PeriodicalId":6877,"journal":{"name":"2014 International Conference on Field-Programmable Technology (FPT)","volume":"28 4 1","pages":"290-291"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"No zero padded sparse matrix-vector multiplication on FPGAs\",\"authors\":\"Jiasen Huang, Junyan Ren, Wenbo Yin, Lingli Wang\",\"doi\":\"10.1109/FPT.2014.7082800\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sparse Matrix-Vector Multiplication (SpMxV) algorithms suffer heavy performance penalties due to irregular memory accesses. In this paper, we introduce a novel compressed element storage (CES) format, in which the additional data structures for indexing are abandoned, and each location associated with the non-zero element of the matrix is now indicated by the name of a variable multiplied by the corresponding element of the vector. To ensure fastest access and parallel access without data hazards, on-chip registers are used exclusively to replace the BRAM or off-chip DRAM/SRAM to hold all the SpMxV data. On-chip DSP resources are fully utilized so as to ensure a maximum number of multipliers concurrently working.\",\"PeriodicalId\":6877,\"journal\":{\"name\":\"2014 International Conference on Field-Programmable Technology (FPT)\",\"volume\":\"28 4 1\",\"pages\":\"290-291\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Field-Programmable Technology (FPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FPT.2014.7082800\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Field-Programmable Technology (FPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPT.2014.7082800","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
No zero padded sparse matrix-vector multiplication on FPGAs
Sparse Matrix-Vector Multiplication (SpMxV) algorithms suffer heavy performance penalties due to irregular memory accesses. In this paper, we introduce a novel compressed element storage (CES) format, in which the additional data structures for indexing are abandoned, and each location associated with the non-zero element of the matrix is now indicated by the name of a variable multiplied by the corresponding element of the vector. To ensure fastest access and parallel access without data hazards, on-chip registers are used exclusively to replace the BRAM or off-chip DRAM/SRAM to hold all the SpMxV data. On-chip DSP resources are fully utilized so as to ensure a maximum number of multipliers concurrently working.