Parameter scan of an effective group difference pseudopotential using grid computing

  • Authors:

  • Wibke Sudholt;Kim K. Baldridge;David Abramson;Colin Enticott;Slavisa Garic

  • Affiliations:

  • Department of Chemistry & Biochemistry and San Diego, Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, Mail Code 0505, La Jolla, CA;Department of Chemistry & Biochemistry and San Diego, Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, Mail Code 0505, La Jolla, CA;School of Computer Science and Software Engineering, Monash University, Clayton, Victoria, 3800 Australia;School of Computer Science and Software Engineering, Monash University, Clayton, Victoria, 3800 Australia;School of Computer Science and Software Engineering, Monash University, Clayton, Victoria, 3800 Australia

  • Venue:
  • New Generation Computing - Grid systems for life sciences
  • Year:
  • 2004

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Abstract

Computational modeling in the health sciences is still very challenging and much of the success has been despite the difficulties involved in integrating all of the technologies, software, and other tools necessary to answer complex questions. Very large-scale problems are open to questions of spatio-temporal scale, and whether physico-chemical complexity is matched by biological complexity. For example, for many reasons, many large-scale biomedical computations today still tend to use rather simplified physics/chemistry compared with the state of knowledge of the actual biology/biochemistry. The ability to invoke modern grid technologies offers the ability to create new paradigms for computing, enabling access of resources which facilitate spanning the biological scale.