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Component-based integration of chemistry and optimization software.

Joseph P Kenny1, Steven J Benson, Yuri Alexeev

  • 1High Performance Computing and Networking Department, Sandia National Laboratories, MS 9915, P.O. Box 969, Livermore, California 94551-0969, USA. jpkenny@sandia.gov

Journal of Computational Chemistry
|September 14, 2004
PubMed
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This study introduces a component architecture for scientific software, enhancing interoperability and collaboration in molecular structure optimization. The new approach allows interchangeable use of diverse chemistry and mathematics packages, improving research capabilities.

Area of Science:

  • Computational Chemistry
  • Software Engineering

Background:

  • Scientific software often faces interoperability challenges due to rigid design assumptions, hindering collaboration.
  • Component-based software engineering offers a solution for managing complexity and promoting code reuse.

Purpose of the Study:

  • To develop a component architecture for molecular structure optimization.
  • To enhance scientific software interoperability and facilitate the integration of diverse computational chemistry and mathematics packages.

Main Methods:

  • Adopted Common Component Architecture Forum methodology and tools.
  • Developed chemistry components using NWChem and Massively Parallel Quantum Chemistry for energy evaluation.
  • Integrated optimization and linear algebra packages (TAO, PETSc, Global Arrays) for geometry optimization applications.

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Main Results:

  • Created interchangeable chemistry and mathematics components through abstract interfaces.
  • Demonstrated good performance of the component software in initial numerical results.
  • Highlighted the potential for new research enabled by this flexible platform.

Conclusions:

  • The developed component architecture successfully addresses scientific software interoperability issues.
  • This approach enables flexible construction of molecular optimization applications with interchangeable packages.
  • The platform shows promise for advancing computational chemistry research through enhanced collaboration and code reuse.