Partitioning and Mapping Algorithms into Fixed Size Systolic Arrays
IEEE Transactions on Computers
VLSI array processors
Massively Parallel Solutions for Molecular Sequence Analysis
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
A Run-Time Reconfigurable System for Gene-Sequence Searching
VLSID '03 Proceedings of the 16th International Conference on VLSI Design
Families of FPGA-Based Algorithms for Approximate String Matching
ASAP '04 Proceedings of the Application-Specific Systems, Architectures and Processors, 15th IEEE International Conference
Hyper customized processors for bio-sequence database scanning on FPGAs
Proceedings of the 2005 ACM/SIGDA 13th international symposium on Field-programmable gate arrays
High-speed Multiple Sequence Alignment on a reconfigurable platform
International Journal of Bioinformatics Research and Applications
Hardware accelerated sequence alignment with traceback
International Journal of Reconfigurable Computing - Special issue on selected papers from ReConFig 2008
Reconfigurable hardware implementation of a multivariate polynomial interpolation algorithm
International Journal of Reconfigurable Computing - Special issue on selected papers from ReconFig 2009 International conference on reconfigurable computing and FPGAs (ReconFig 2009)
FPGA-based smith-waterman algorithm: analysis and novel design
ARC'11 Proceedings of the 7th international conference on Reconfigurable computing: architectures, tools and applications
Parametrizing multicore architectures for multiple sequence alignment
Proceedings of the 8th ACM International Conference on Computing Frontiers
Microprocessors & Microsystems
High performance biological pairwise sequence alignment: FPGA versus GPU versus cell BE versus GPP
International Journal of Reconfigurable Computing - Special issue on High-Performance Reconfigurable Computing
Optimization schemes and performance evaluation of Smith–Waterman algorithm on CPU, GPU and FPGA
Concurrency and Computation: Practice & Experience
Efficient architecture and scheduling technique for pairwise sequence alignment
ACM SIGARCH Computer Architecture News
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A Hardware Viewpoint on Biosequence Analysis: What’s Next?
ACM Journal on Emerging Technologies in Computing Systems (JETC) - Special Issue on Bioinformatics
Hi-index | 0.00 |
This paper presents the design and implementation of the most parameterisable field-programmable gate array (FPGA)-based skeleton for pairwise biological sequence alignment reported in the literature. The skeleton is parameterised in terms of the sequence symbol type, i.e., DNA, RNA, or Protein sequences, the sequence lengths, the match score, i.e., the score attributed to a symbol match, mismatch or gap, and the matching task, i.e., the algorithm used to match sequences, which includes global alignment, local alignment, and overlapped matching. Instances of the skeleton implement the Smith-Waterman and the Needleman-Wunsch Algorithms. The skeleton has the advantage of being captured in the Handel-C language, which makes it FPGA platform-independent. Hence, the same code could be ported across a variety of FPGA families. It implements the sequence alignment algorithm in hand using a pipeline of basic processing elements, which are tailored to the algorithm parameters. This paper presents a number of optimizations built into the skeleton and applied at compile-time depending on the user-supplied parameters. These result in high performance FPGA implementations tailored to the algorithm in hand. For instance, actual hardware implementations of the Smith-Waterman algorithm for Protein sequence alignment achieve speedups of two orders of magnitude compared to equivalent standard desktop software implementations.