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Multiprocessor Sequence Alignment

  • Tieng K. Yap
  • Ophir Frieder
  • Robert L. Martino

Abstract

As stated in Chapter 3, the Human Genome Project has generated a massive volume of sequence data. Furthermore, longer sequences are being generated due to recent advances in sequencing technology. Consequently, the computational performance needed to analyze these new sequences is increasing enormously. It is presently impractical to align two long sequences or to align a large number of sequences of moderate length on a traditional single processor computer. To meet these computational demands, the high performance provided by parallel computers must be exploited.

Keywords

Parallel Algorithm Optimal Path Idle Time Speedup Factor Cluster Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Tieng K. Yap
    • 1
  • Ophir Frieder
    • 2
  • Robert L. Martino
    • 1
  1. 1.National Institutes of HealthBethesdaUSA
  2. 2.George Mason UniversityFairfaxUSA

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