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Massively parallel FPGA-based implementation of BLASTp with the two-hit method

机译:基于两次命中方法的基于大规模并行FPGA的BLASTp实现

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Protein database search requests are generally being performed using the BLASTp algorithm, introduced by NCBI [1]. Since it is computationally intensive, it becomes more and more ine_ective with today's growth of sequence database sizes. The needs for an e_cient parallel implementation arise. In this paper, we focus on a massive parallelization using the FPGA-based hardware architecture RIVYERA [2]. The aim is to reach speedups in orders of magnitude with a flexible implementation while saving energy costs compared to PC-based database search. We keep our implementation close to the structure published by Kasap et al. [3,4] and include ideas from Sotiriades et al. [5] such that all parts of the algorithm are organized in components of a long pipeline. We also use the idea of the two-hit method [6] to keep the computational e_ort small. Besides the related work, we perform the very last step of the algorithm to produce a gapped alignment with the Needleman-Wunsch algorithm in software, only with the option of hardware processing after reconfiguration. This saves FPGA-resources and allows an even higher degree of parallelism.
机译:蛋白质数据库搜索请求通常使用NCBI [1]引入的BLASTp算法执行。由于它的计算量很大,因此随着当今序列数据库大小的增长,它变得越来越无效。出现了对有效的并行实现的需求。在本文中,我们专注于使用基于FPGA的硬件架构RIVYERA [2]进行大规模并行化。与基于PC的数据库搜索相比,其目标是通过灵活的实现方式实现数量级的加速,同时节省能源成本。我们将实现保持与Kasap等人发布的结构接近。 [3,4]并包括Sotiriades等人的观点。 [5]这样,算法的所有部分都组织在长管道的组件中。我们还使用两次命中方法的思想[6]来保持计算的e_ort小。除了相关工作之外,我们还执行算法的最后一步,以便在软件中与Needleman-Wunsch算法产生间隙对齐,仅在重新配置后选择硬件处理。这样可以节省FPGA资源,并允许更高程度的并行性。

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