{"title":"基于smith - waterman DNA序列比对的优化和便携式fpga收缩细胞结构","authors":"Hurmat Ali Shah, L. Hasan, Insoo Koo","doi":"10.6109/jicce.2016.14.1.026","DOIUrl":null,"url":null,"abstract":"The alignment of DNA sequences is one of the important processes in the field of bioinformatics. The Smith–Waterman algorithm (SWA) performs optimally for aligning sequences but is computationally expensive. Field programmable gate array (FPGA) performs the best on parameters such as cost, speed-up, and ease of re-configurability to implement SWA. The performance of FPGA-based SWA is dependent on efficient cell-basic implementation-unit design. In this paper, we present an optimized systolic cell design while avoiding oversimplification, very large-scale integration (VLSI)-level design, and direct mapping of iterative equations such as previous cell designs. The proposed design makes efficient use of hardware resources and provides portability as the proposed design is not based on gate-level details. Our cell design implementing a linear gap penalty resulted in a performance improvement of 32× over a GPP platform and surpassed the hardware utilization of another implementation by a factor of 4.23.","PeriodicalId":272551,"journal":{"name":"J. Inform. and Commun. Convergence Engineering","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Optimized and Portable FPGA-Based Systolic Cell Architecture for Smith-Waterman-Based DNA Sequence Alignment\",\"authors\":\"Hurmat Ali Shah, L. Hasan, Insoo Koo\",\"doi\":\"10.6109/jicce.2016.14.1.026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The alignment of DNA sequences is one of the important processes in the field of bioinformatics. The Smith–Waterman algorithm (SWA) performs optimally for aligning sequences but is computationally expensive. Field programmable gate array (FPGA) performs the best on parameters such as cost, speed-up, and ease of re-configurability to implement SWA. The performance of FPGA-based SWA is dependent on efficient cell-basic implementation-unit design. In this paper, we present an optimized systolic cell design while avoiding oversimplification, very large-scale integration (VLSI)-level design, and direct mapping of iterative equations such as previous cell designs. The proposed design makes efficient use of hardware resources and provides portability as the proposed design is not based on gate-level details. Our cell design implementing a linear gap penalty resulted in a performance improvement of 32× over a GPP platform and surpassed the hardware utilization of another implementation by a factor of 4.23.\",\"PeriodicalId\":272551,\"journal\":{\"name\":\"J. Inform. and Commun. Convergence Engineering\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"J. Inform. and Commun. Convergence Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.6109/jicce.2016.14.1.026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Inform. and Commun. Convergence Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6109/jicce.2016.14.1.026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimized and Portable FPGA-Based Systolic Cell Architecture for Smith-Waterman-Based DNA Sequence Alignment
The alignment of DNA sequences is one of the important processes in the field of bioinformatics. The Smith–Waterman algorithm (SWA) performs optimally for aligning sequences but is computationally expensive. Field programmable gate array (FPGA) performs the best on parameters such as cost, speed-up, and ease of re-configurability to implement SWA. The performance of FPGA-based SWA is dependent on efficient cell-basic implementation-unit design. In this paper, we present an optimized systolic cell design while avoiding oversimplification, very large-scale integration (VLSI)-level design, and direct mapping of iterative equations such as previous cell designs. The proposed design makes efficient use of hardware resources and provides portability as the proposed design is not based on gate-level details. Our cell design implementing a linear gap penalty resulted in a performance improvement of 32× over a GPP platform and surpassed the hardware utilization of another implementation by a factor of 4.23.