基于smith - waterman DNA序列比对的优化和便携式fpga收缩细胞结构

Hurmat Ali Shah, L. Hasan, Insoo Koo
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引用次数: 5

摘要

DNA序列比对是生物信息学领域的重要过程之一。Smith-Waterman算法(SWA)在序列对齐方面性能最佳,但计算量大。现场可编程门阵列(FPGA)在成本、加速和易于重新配置等参数上表现最佳,以实现SWA。基于fpga的SWA的性能取决于高效的cell-basic实现单元设计。在本文中,我们提出了一个优化的收缩细胞设计,同时避免了过度简化,超大规模集成(VLSI)级设计,以及迭代方程的直接映射,如以前的细胞设计。所提出的设计有效地利用了硬件资源,并提供了可移植性,因为所提出的设计不基于门级细节。我们的单元设计实现了线性间隙惩罚,导致性能比GPP平台提高了32倍,并且超过了另一种实现的硬件利用率4.23倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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