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Related Experiment Videos

Computational chemistry on commodity-type computers

M C Nicklaus1, R W Williams, B Bienfait

  • 1Laboratory of Medicinal Chemistry, National Cancer Institute, National Institutes of Health (NIH), Bethesda, Maryland 20892-4255, USA.

Journal of Chemical Information and Computer Sciences
|October 14, 1998
PubMed
Summary
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Inexpensive computers running density functional theory (DFT) calculations on Linux systems can outperform supercomputers. Compiler choice significantly impacts performance, more than hardware, on these commodity systems.

Area of Science:

  • Computational Chemistry
  • High-Performance Computing

Background:

  • Ab initio quantum chemistry methods, such as density functional theory (DFT), require significant computational resources.
  • The increasing availability of inexpensive commodity hardware presents an alternative to traditional supercomputing for scientific research.

Purpose of the Study:

  • To benchmark the performance of various inexpensive computers using the Gaussian 94 program.
  • To compare the computational speed of commodity hardware against established workstations and supercomputers for DFT calculations.

Main Methods:

  • Benchmarking of Pentium (x86) and Alpha CPU systems running Linux.
  • Execution of small standard test jobs and larger DFT calculations using Gaussian 94.
  • Comparison of job CPU times across different hardware, operating systems, and compiler configurations.

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Main Results:

  • Powerful commodity processors demonstrated speeds exceeding current supercomputers.
  • Compiler choice and options had a greater impact on job CPU times than hardware specifics.
  • On x86 systems, reduced RAM allocation correlated with faster job execution.
  • An Alpha/Linux system achieved the highest per-CPU speed, outperforming a Cray J90 for DFT calculations.

Conclusions:

  • Commodity hardware, particularly Alpha/Linux systems, offers a cost-effective and high-performance alternative for computational chemistry.
  • Optimizing compilers and compilation settings is crucial for maximizing computational efficiency on these systems.
  • The performance gains suggest a shift in high-performance computing strategies towards accessible hardware solutions.