BENCHMARKING AND PARALLEL ALGORITHM IMPROVEMENT FOR CHARMM WITH AN APPLICATION

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Although a number of faster basic molecular dynamics (MD) algorithms exist, none have nearly as many fully implemented sampling methods as CHARMM. The advanced sampling methods in CHARMM are critical for meaningful molecular simulation, especially for large biomolecules. Improvement of the parallel implementation of the CHARMM MD engine to fully take advantage of modern massively parallel architecture will allow CHARMM to match the performance of other top MD programs. We need more large supercomputer resources and architectures to test and develop the algorithm. Our specific scientific project (carbohydrate modeling) and the larger CHARMM user community will greatly benefit from this development. Carbohydrate modeling connects to one of our large SciDAC grants to understand the biochemical mechanism in enzyme-catalyzed cellulose degradation, in which carbohydrate recognition and glycosylation play important roles.