Proceedings Article10.1145/1046192.1046222
Hyper customized processors for bio-sequence database scanning on FPGAs
Tim Oliver,Bertil Schmidt,Douglas L. Maskell +2 more
- 20 Feb 2005
- pp 229-237
TL;DR: This paper presents a new approach to bio-sequence database scanning using re-configurable FPGA-based hardware platforms to gain high performance at low cost and shows how hyper-customization at run-time can be used to further improve the performance.
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Abstract: Protein sequences with unknown functionality are often compared to a set of known sequences to detect functional similarities. Efficient dynamic-programming algorithms exist for solving this problem, however current solutions still require significant scan times. These scan time requirements are likely to become even more severe due to exponential database growth. In this paper we present a new approach to bio-sequence database scanning using re-configurable FPGA-based hardware platforms to gain high performance at low cost. Efficient mappings of the Smith-Waterman algorithm using fine-grained parallel processing elements (PEs) that are tailored towards the parameters of a query have been designed. We use customization opportunities available at run-time to dynamically hyper customize the systolic array to make better use of available resource. Our FPGA implementation achieves a speedup of approximately 170 for linear gap penalties and 125 for affine gap penalties as compared to a standard desktop computing platform. We show how hyper-customization at run-time can be used to further improve the performance.
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Bioinformatics systems, apparatuses, and methods executed on an integrated circuit processing platform
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An FPGA-based systolic array to accelerate the BWA-MEM genomic mapping algorithm
Ernst Joachim Houtgast,Vlad-Mihai Sima,Koen Bertels,Zaid Al-Ars +3 more
- 19 Jul 2015
TL;DR: This work presents the first accelerated implementation of BWA-MEM, a popular genome sequence alignment algorithm widely used in next generation sequencing genomics pipelines, and proposes and evaluates a number of FPGA-based systolic array architectures, presenting optimizations generally applicable to variable length Smith-Waterman execution.
FPGASW: Accelerating Large-Scale Smith–Waterman Sequence Alignment Application with Backtracking on FPGA Linear Systolic Array
TL;DR: This paper proposes fine-grained parallelized SW algorithms using affine gap penalty and implements a parallel computing structures to accelerating the SW with backtracking on FPGA platform, and analysis the dynamic parallel computing features of anti-diagonal elements and storage expansion problem resulting from backtracking stage.
66
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