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A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

GPU-BLAST: using graphics processors to accelerate protein sequence alignment.

Panagiotis D Vouzis¹, Nikolaos V Sahinidis

¹Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Bioinformatics (Oxford, England)

|November 20, 2010

Summary

This summary is machine-generated.

GPU-BLAST accelerates the popular Basic Local Alignment Search Tool (BLAST) using graphics processing units (GPUs). This enhanced version maintains identical results while achieving 3-4x speedups for faster biological sequence comparison.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

The Basic Local Alignment Search Tool (BLAST) is a cornerstone bioinformatics tool with over 53,000 citations.
Its widespread use necessitates improvements in execution speed to handle growing biomolecular databases.

Purpose of the Study:

To develop an accelerated version of NCBI-BLAST.
To leverage graphics processing units (GPUs) for enhanced computational efficiency.

Main Methods:

Developed GPU-BLAST, an accelerated version of NCBI-BLAST.
Utilized general-purpose graphics processing units (GPUs) for implementation.
Maintained the original NCBI-BLAST source code for compatibility.

Main Results:

GPU-BLAST achieves speedups ranging from 3 to 4 times compared to sequential NCBI-BLAST.
The implementation produces identical results to the original NCBI-BLAST.
The source code for GPU-BLAST is publicly available.

Conclusions:

GPU-BLAST offers significant performance improvements for biological sequence comparison.
This acceleration facilitates handling of large-scale biomolecular data.
The tool maintains accuracy and compatibility with existing BLAST workflows.