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BLASTP-ACC: Parallel Architecture and Hardware Accelerator Design for BLAST-Based Protein Sequence Alignment.

Yu-Cheng Li, Yi-Chang Lu

    IEEE Transactions on Biomedical Circuits and Systems
    |October 4, 2019
    PubMed
    Summary

    This study introduces a hardware accelerator for the Basic Local Alignment Search Tool for Proteins (BLASTP), achieving over 500 GCUPS. The new design significantly speeds up protein sequence alignment compared to traditional software.

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    Area of Science:

    • Bioinformatics
    • Computer Engineering
    • Computational Biology

    Background:

    • Sequence alignment is crucial for understanding protein function and evolution.
    • Existing software implementations of algorithms like BLASTP can be computationally intensive.
    • Hardware acceleration offers a potential solution for speeding up these critical bioinformatics tasks.

    Purpose of the Study:

    • To design and implement a novel hardware accelerator for the BLASTP algorithm.
    • To improve the processing speed and efficiency of protein sequence alignment.
    • To enable faster analysis of large protein sequence databases.

    Main Methods:

    • Developed a five-stage hardware architecture including systolic-array and RAM-REG based stages.
    • Implemented the accelerator on an Altera Stratix V FPGA.
    • Utilized a novel parallel sorter for efficient result ordering.
    • Tested performance using data from the National Center for Biotechnology Information (NCBI) database.

    Main Results:

    • Achieved a processing speed exceeding 500 giga cell updates per second (GCUPS).
    • Demonstrated a speed-up of over 3X compared to multi-threaded CPU software.
    • Successfully processed long protein sequences (up to 8192 residues) in a single pass.
    • Generated a similarity score-sorted list of aligned sequences.

    Conclusions:

    • The proposed hardware accelerator significantly enhances BLASTP performance.
    • This hardware-based approach offers a substantial speed advantage for large-scale sequence alignment.
    • The design is capable of handling complex and lengthy protein sequence comparisons efficiently.