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Related Experiment Videos

A multithreaded parallel implementation of a dynamic programming algorithm for sequence comparison.

W S Martins1, J B Del Cuvillo, F J Useche

  • 1Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|March 27, 2001
PubMed
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This study demonstrates efficient parallel implementation of dynamic programming for biological sequence comparison using fine-grain multithreading. High performance and scalability were achieved on the EARTH system.

Area of Science:

  • Computational Biology
  • Computer Science
  • Parallel Computing

Background:

  • Biological sequence comparison is computationally intensive.
  • Dynamic programming algorithms are commonly used but can be slow.
  • Parallel computing offers potential for performance improvement.

Purpose of the Study:

  • To address the challenges of implementing dynamic programming for biological sequence comparison on parallel platforms.
  • To evaluate a fine-grain event-driven multithreaded execution model for this task.

Main Methods:

  • Implementation of a dynamic programming algorithm using a fine-grain event-driven multithreaded execution model.
  • Utilizing the EARTH system, a multithreaded execution and architecture model.
  • Porting the scheme to parallel machines with off-the-shelf processors.

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Main Results:

  • Efficient parallelism exploitation through low-overhead asynchronous communication and synchronization.
  • Effective latency tolerance by overlapping computation and communication.
  • Achieved high performance, with a speedup of 90 on 120 nodes.

Conclusions:

  • Dynamic programming for biological sequence comparison can be efficiently implemented on EARTH systems.
  • The approach offers high performance, good programmability, and reasonable cost.
  • Fine-grain multithreading is a viable strategy for accelerating biological sequence analysis.