Biomolecular Modeling using Parallel Supercomputers
Handbook of Computational Molecular Biology 2005
Publication Type: Paper
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Abstract
Our knowledge of molecular biology and the machinery of life has
been increasing in leaps and bounds. To coalesce this knowledge
into a deeper understanding, we need to determine the structure of
a multitude of proteins with high resolution, and understand the
relationship between their structure and function. Molecular
dynamics simulations help further this understanding by allowing us
to observe dynamical phenomena occurring at an atomic level, and
validate our understanding of the basic physical principles
embodied in simulations. Simulations based on classical mechanics,
with some approximations of the quantum-mechanical "reality'' are
adequate for many situations; however, for simulations involving
making and breaking of bonds, for example, a quantum mechanical
simulation is necessary. The Car-Parinello algorithm and the
ability to combine classical and quantum models in a single
simulation are efficient ways of accomplishing this. In either
case, the computational power needed for carrying out the
simulations over an interesting interval of time of the
biomolecular phenomena is so large that only parallel computers
offer the hope of completing such simulations in a realistic time.
Although large parallel computers are available now, it is quite
challenging to parallelize the simulations so as to scale to
thousands of processors and beyond. This paper presented an
overview of strategies aimed at this problem, and presented in some
detail the particular strategies the authors have been pursuing.
TextRef
Laxmikant V. Kale and Klaus Schulten and Robert D. Skeel and Glenn Martyna
and Mark Tuckerman and James C. Phillips and Sameer Kumar and Gengbin Zheng,
"Biomolecular modeling using parallel supercomputers", Handbook of computational
molecular biology, 2005. Editor S. Aluru, Publ: Taylor and Francis, pp. 34.1-34.43.
People
- Laxmikant Kale
- Klaus Schulten
- Robert Skeel
- Glenn Martyna
- Mark Tuckerman
- James Phillips
- Sameer Kumar
- Gengbin Zheng
Research Areas