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Related Experiment Videos

High performance computing for the human genome project

K Böhm1

  • 1Department of Central Data Processing, Deutsches Krebsforschungszentrum, Heidelberg.

Computer Methods and Programs in Biomedicine
|February 1, 1995
PubMed
Summary
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High-performance computing challenges in human genome analysis and image processing necessitate scalable parallel systems. Evaluating these new systems with application benchmarks demonstrates their superior price/performance over traditional mainframes for biocomputing.

Area of Science:

  • High Performance Computing
  • Biocomputing
  • Genomics

Background:

  • Traditional mainframes are insufficient for complex Human Genome Analysis and Image Processing tasks.
  • Advancements in scalable parallel processor systems offer improved price/performance ratios.

Purpose of the Study:

  • To evaluate the performance of new scalable parallel processor systems for biocomputing applications.
  • To assess the suitability of these systems for 'Grand Challenges' in High Performance Computing.

Main Methods:

  • Development and application of an application-oriented benchmark test suite.
  • Integration of the evaluated system within a client/server architecture.
  • Performance assessment focusing on price/performance metrics.

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Main Results:

  • New scalable parallel systems demonstrate superior price/performance compared to traditional mainframes.
  • The benchmark test suite effectively evaluated system capabilities for biocomputing.

Conclusions:

  • Scalable parallel systems are a viable and cost-effective replacement for mainframes in biocomputing.
  • The Deutsches Krebsforschungszentrum is positioned to eliminate mainframe dependency through 'rightsizing'.