{"title":"在fpga增强型PC集群上加速BLAST计算","authors":"Masato Yoshimi, Celimuge Wu, T. Yoshinaga","doi":"10.1109/CANDAR.2016.0025","DOIUrl":null,"url":null,"abstract":"This paper introduces an FPGA-based scheme to accelerate mpiBLAST, which is a parallel sequence alignment algorithm for computational biology. Recent rapidly growing biological databases for sequence alignment require high-throughput storage and network rather than computing speed. Our scheme utilizes a specialized hardware configured on an FPGA-board which connects flash storage and other FPGA-boards directly. The specialized hardware configured on the FPGAs, we call a Data Stream Processing Engine (DSPE), take a role for preprocessing to adjust data for high-performance multi- and many- core processors simultaneously with offloading system-calls for storage access and networking. DSPE along the datapath achieves in-datapath computing which applies operations for data streams passing through the FPGA. Two functions in mpiBLAST are implemented using DSPE to offload operations along the datapath. The first function is database partitioning, which distributes the biological database to multiple computing nodes before commencing the BLAST processes. Using DSPE, we observe a 20-fold improvement in computation time for the database partitioning operation. The second function is an early part of the BLAST process that determines the positions of sequences for more detailed computations. We implement IDP-BLAST (In-datapath BLAST), which annotates positions in data streams from solid-state drives. We show that IDP-BLAST accelerates the computation time of the preprocess of BLAST by a factor of three hundred by offloading heavy operations to the introduced special hardware.","PeriodicalId":322499,"journal":{"name":"2016 Fourth International Symposium on Computing and Networking (CANDAR)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Accelerating BLAST Computation on an FPGA-enhanced PC Cluster\",\"authors\":\"Masato Yoshimi, Celimuge Wu, T. Yoshinaga\",\"doi\":\"10.1109/CANDAR.2016.0025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces an FPGA-based scheme to accelerate mpiBLAST, which is a parallel sequence alignment algorithm for computational biology. 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Using DSPE, we observe a 20-fold improvement in computation time for the database partitioning operation. The second function is an early part of the BLAST process that determines the positions of sequences for more detailed computations. We implement IDP-BLAST (In-datapath BLAST), which annotates positions in data streams from solid-state drives. 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引用次数: 6
摘要
mpiBLAST是一种用于计算生物学的并行序列比对算法,本文介绍了一种基于fpga的加速方案。最近快速发展的生物序列比对数据库需要高通量存储和网络,而不是计算速度。我们的方案利用fpga板上配置的专用硬件直接连接闪存和其他fpga板。在fpga上配置的专用硬件,我们称之为数据流处理引擎(Data Stream Processing Engine, DSPE),承担预处理的角色,为高性能多核和多核处理器调整数据,同时卸载存储访问和网络的系统调用。沿着数据路径的DSPE实现了对经过FPGA的数据流进行运算的数据路径内计算。mpiBLAST中的两个函数是使用DSPE实现的,用于沿着数据路径卸载操作。第一个功能是数据库分区,它在开始BLAST进程之前将生物数据库分发到多个计算节点。使用DSPE,我们观察到数据库分区操作的计算时间提高了20倍。第二个函数是BLAST过程的早期部分,用于确定序列的位置,以便进行更详细的计算。我们实现了IDP-BLAST (in -datapath BLAST),它注释了来自固态驱动器的数据流中的位置。通过将繁重的操作转移到引入的专用硬件上,IDP-BLAST将BLAST预处理的计算时间提高了300倍。
Accelerating BLAST Computation on an FPGA-enhanced PC Cluster
This paper introduces an FPGA-based scheme to accelerate mpiBLAST, which is a parallel sequence alignment algorithm for computational biology. Recent rapidly growing biological databases for sequence alignment require high-throughput storage and network rather than computing speed. Our scheme utilizes a specialized hardware configured on an FPGA-board which connects flash storage and other FPGA-boards directly. The specialized hardware configured on the FPGAs, we call a Data Stream Processing Engine (DSPE), take a role for preprocessing to adjust data for high-performance multi- and many- core processors simultaneously with offloading system-calls for storage access and networking. DSPE along the datapath achieves in-datapath computing which applies operations for data streams passing through the FPGA. Two functions in mpiBLAST are implemented using DSPE to offload operations along the datapath. The first function is database partitioning, which distributes the biological database to multiple computing nodes before commencing the BLAST processes. Using DSPE, we observe a 20-fold improvement in computation time for the database partitioning operation. The second function is an early part of the BLAST process that determines the positions of sequences for more detailed computations. We implement IDP-BLAST (In-datapath BLAST), which annotates positions in data streams from solid-state drives. We show that IDP-BLAST accelerates the computation time of the preprocess of BLAST by a factor of three hundred by offloading heavy operations to the introduced special hardware.