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Related Experiment Video

Updated: Jun 27, 2026

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Published on: June 28, 2017

Single Pass Streaming BLAST on FPGAs.

Martin C Herbordt¹, Josh Model, Bharat Sukhwani

¹Department of Electrical and Computer Engineering, Boston University; Boston, MA 02215, Web: http://www.bu.edu/caadlab .

Parallel Computing

|December 17, 2008

Summary

This summary is machine-generated.

This study introduces novel FPGA acceleration algorithms for bioinformatics, enhancing both BLAST and dynamic programming methods. New algorithms achieve significant speedups for approximate string matching in large databases.

Related Experiment Videos

Last Updated: Jun 27, 2026

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Published on: June 28, 2017

Area of Science:

Bioinformatics
Computer Science
Hardware Acceleration

Background:

Approximate string matching is crucial in bioinformatics.
Field-Programmable Gate Arrays (FPGAs) are widely studied for accelerating these computations.
Existing FPGA implementations of BLAST and dynamic programming (DP) methods have limitations.

Purpose of the Study:

To address limitations in FPGA implementations of BLAST and DP-based approximate string matching.
To develop novel algorithms for efficient FPGA acceleration in bioinformatics.

Main Methods:

Developed a new algorithm for emulating BLAST's seeding and extension phases in a single pass.
Introduced a new data extraction structure for DP-based methods.
Implemented and evaluated algorithms on FPGA hardware.

Main Results:

The new BLAST emulation algorithm processes databases at streaming rates with minimal preprocessing.
Achieved maximum sensitivity without performance degradation.
The DP method's data extraction structure simplifies result generation.
Demonstrated order-of-magnitude acceleration compared to serial implementations.

Conclusions:

The developed FPGA algorithms offer significant performance improvements for approximate string matching.
The new methods enhance the efficiency and applicability of BLAST and DP in bioinformatics.
The approach ensures compatibility with existing tools like NCBI BLAST.