Abstract
The need and possibility for high performance computing (HPC) in molecular modeling are explained in this chapter. This chapter explains HPC as a technique for providing the foundation to meet the data and computing demands of R&D grids. HPC helps in harnessing data and computer resources in a multi-site, multi-organizational context-effective cluster management, making use of maximum computing investment for molecular modeling. Cluster computing and grid computing methodologies are explained.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Feller D (1997) The EMSL Ab Initio Methods Benchmark Report: A Measure of Hardware and Software Performance in the Area of Electronic Structure Methods, Pacific Northwest National Laboratory technical report PNNL-10481 (Version 3.0). http://www.emsl.pnl.gov:2080/docs/tms/abinitio/cover.html
Center of Excellence in Space Data and Information Sciences (CESDIS), NASA Goddard Space Flight Center Beowulf Project at CESDIS, http://www.beowulf.org/
Becker DJ et al. (1995) BEOWULF: A Parallel Workstation for Scientific Computation. Proc Int Conf on Parallel Processing, Aug 1995 1:11–14
Ridge D et al. (1997) Beowulf: Harnessing the Power of Parallelism in a Pile-of-PCs. Proc. IEEE Aerospace
Beowulf Project, Beowulf Consortium, http://www.beowulf.org/consortium.html
Tirado-Rives J, Jorgensen WL (1996) Viability of Molecular Modeling with Pentium based PCs. J Comp Chem 17:11 pp 1385–86
Nicklaus MC, Williams RW, Bienfait B, Billings ES, Hodoscek M (1998) Computational Chemistry on Commodity-Type Computers. J Chem Info Comp Sci 38:5 pp 893–905
Windus TL, Schmidt MW, Gordon MS (1995) Parallel Processing With the Ab Initio Program GAMESS. In: Toward Teraflop Computing and New Grand Challenge Applications, Kalia RJ, Vashishta, eds., Nova Science Publishers, New York
Oak Ridge National Laboratory PVM: Parallel Virtual Machine, http://www.epm.ornl.gov/pvm/pvm_home.html
Anderson TE et al. (1995) A Case for NOW (Networks of Workstations). IEEE Micro Feb pp 54-64
Supercomputer Research Institute, Florida State University DQS - Distributed Queueing System, http://www.scri.fsu.edu/∼pasko/dqs.html
Litzkow M, Livny M, Mutka MW (1988) Condor – A Hunter of Idle Workstations. Proc 8th Int Conf Distr Comp Sys, June 1988, pp 104–111
Distributed and High-Performance Computing Group, University of Adelaide Perseus: AÂ Beowulf for computational chemistry, http://www.dhpc.adelaide.edu.au/projects/beowulf/perseus.html
Karplus M, Chemistry at HARvard Macromolecular Mechanics (CHARMM), http://yuri.harvard.edu/charmm/charmm.html
Gaussian, Inc. and Scientific Computing Associates Highly Efficient Parallel Computation of Very Accurate Chemical Structures and Properties with Gaussian and the Linda Parallel Execution Environment, http://www.gaussian.com/wp_linda.htm
Hockney RW, Jesshope CR (1988) Parallel Computers 2. Adam Hilger, Bristol
Guest MF, Sherwood P, Nichols JA, Massive Parallelism: The Hardware for Computational Chemistry?, http://www.dl.ac.uk/CFS/parallel/MPP/mpp.html
Center of Excellence in Space Data and Information Sciences (CESDIS), NASA Goddard Space Flight Center BPROC: Beowulf Distributed Process Space, http://www.beowulf.org/software/bproc.html
Krauss M, Stevens WJ (1984) Ann Rev Phys Chem 35:357
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
(2008). High Performance Computing. In: Computational Chemistry and Molecular Modeling. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77304-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-77304-7_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77302-3
Online ISBN: 978-3-540-77304-7
eBook Packages: Chemistry and Materials ScienceChemistry and Material Science (R0)