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CHARMM Modernization, Performance, and Continued Development

$394,280R01FY2014GMNIH

University Of Michigan At Ann Arbor, Ann Arbor MI

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Abstract

DESCRIPTION (provided by applicant): CHARMM (Chemistry at Harvard Macromolecular Mechanics) has been a primary research tool for macromolecular simulations and modeling in biology for over two decades. During this period CHARMM development, and applications emerging from its use, have defined the field of biomolecular computation. This proposal is aimed at ensuring CHARMM will continue as the development platform for future generations of scientists by addressing components of the software and its attendant support infrastructure that represent bottlenecks in development, performance and maintenance. Specifically, restructuring the code will provide improvements to underlying computational kernels in CHARMM, which will significantly enhance single processor performance and improve parallel scaling. Emphasis will be given to improving parallelism for two target system sizes. For systems of 50-200K atoms, which represent many typical applications, we will develop, adapt and deploy methods that yield good parallel efficiency (greater than 70%) for tightly coupled parallelism in molecular dynamics on department accessible parallel platforms (~100 commodity processors with a high bandwidth interconnect). For large biological problems on large supercomputers, i.e. for systems approaching 1M atoms running on 0.5-2K processors, we will develop and implement new simulation kernels for CHARMM that exploit the large spatial dimensions of these systems and employ techniques of spatial decomposition and task-level parallelism. Finally, we will develop and improve code and algorithms allowing graphics processor based acceleration to be utilized for the family of CHARMM potentials and methods. The outcome of these efforts will be a program platform that will facilitate continued forefront research in macromolecular simulation and modeling and enable its continued development and maintenance for future generations of researchers.

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