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Related Experiment Video

Updated: Jun 1, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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Published on: April 12, 2019

Faster Smith-Waterman database searches with inter-sequence SIMD parallelisation.

Torbjørn Rognes1

  • 1Department of Informatics, University of Oslo, PO Box 1080 Blindern, NO-0316 Oslo, Norway. torognes@ifi.uio.no

BMC Bioinformatics
|June 3, 2011
PubMed
Summary
This summary is machine-generated.

A new tool, SWIPE, accelerates Smith-Waterman sequence alignment using parallel processing. This significantly speeds up local alignment searches, making them more practical for large-scale biological data analysis.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • The Smith-Waterman algorithm offers high sensitivity for local sequence alignment but is computationally intensive.
  • Previous parallelization efforts using SIMD technology by Farrar (2007) improved speed but left room for further optimization.

Purpose of the Study:

  • To investigate novel parallelization approaches for the Smith-Waterman algorithm to achieve greater speed improvements.
  • To develop and benchmark a new implementation for faster local sequence alignment.

Main Methods:

  • Developed SWIPE, a new implementation of the Smith-Waterman algorithm.
  • Implemented parallel processing where multiple database sequences are compared against a single query sequence using SIMD technology.
  • Benchmarked SWIPE performance on a dual Intel Xeon X5650 system, comparing it against Farrar's approach and BLAST.

Main Results:

  • SWIPE achieved 106 billion cell updates per second (GCUPS) for a 375-residue query, exceeding Farrar's method by over six times.
  • SWIPE demonstrated significant speedups, especially for shorter query sequences and in single-threaded performance (2.5x faster).
  • Performance comparisons showed SWIPE was twice as fast as BLAST with the BLOSUM50 matrix, while BLAST was faster with BLOSUM62.

Conclusions:

  • Efficient parallelization of Smith-Waterman using SIMD on standard hardware enables over sixfold speed increases.
  • The SWIPE approach can substantially expand the applicability of Smith-Waterman searches in bioinformatics.
  • This optimized local alignment method has potential benefits for other applications requiring optimal alignment scores.