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H-BLAST: a fast protein sequence alignment toolkit on heterogeneous computers with GPUs.

Weicai Ye1, Ying Chen1, Yongdong Zhang1

  • 1School of Data and Computer Science, and Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou 510275, People's Republic of China.

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Heterogeneous BLAST (H-BLAST) accelerates sequence alignment by coupling CPUs and GPUs, offering significant speedups over traditional NCBI-BLAST and GPU-BLAST for large bio-sequence databases.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • High-Performance Computing

Background:

  • Sequence alignment is crucial in bioinformatics.
  • BLAST is a widely used tool, but its speed needs improvement due to exponentially growing databases.
  • Existing tools struggle to keep pace with increasing data volumes.

Purpose of the Study:

  • To develop a faster parallel search tool for sequence alignment.
  • To accelerate BLASTX and BLASTP using heterogeneous computing (CPUs and GPUs).
  • To improve computational efficiency for large-scale bio-sequence analysis.

Main Methods:

  • Developed heterogeneous BLAST (H-BLAST), a parallel search tool utilizing CPUs and GPUs.
  • Implemented a locally decoupled seed-extension algorithm optimized for GPUs.
  • Integrated a performance tuning mechanism for diverse CPU-GPU combinations.

Main Results:

  • H-BLAST achieves identical alignment results to NCBI-BLAST.
  • Demonstrated significant speedups: 4-10x for BLASTP and 5-7.2x for BLASTX over sequential NCBI-BLAST.
  • H-BLAST with 2 CPU threads and 2 GPUs outperforms 16-threaded NCBI-BLASTX.
  • Achieved 1.5-4x speedup compared to GPU-BLAST.

Conclusions:

  • H-BLAST significantly enhances the speed of sequence alignment on heterogeneous systems.
  • The tool provides a viable solution for accelerating BLAST searches in the era of big biological data.
  • H-BLAST offers a practical and efficient alternative for researchers needing faster alignment.