TY - CHAP
T1 - GPU-accelerated computation and interactive display of molecular orbitals
AU - Stone, John E.
AU - Hardy, David J.
AU - Saam, Jan
AU - Vandivort, Kirby L.
AU - Schulten, Klaus
N1 - Funding Information:
This work was supported by the National Institutes of Health, under grant P41-RR05969. Portions of this chapter © 2009 Association for Computing Machinery, Inc. Reprinted by permission [1] .
PY - 2011
Y1 - 2011
N2 - This chapter presents several graphics processing unit (GPU) algorithms for evaluating molecular orbitals on three-dimensional lattices, as is commonly used for molecular visualization. The GPU kernels described here form the basis for the high-performance molecular orbital display algorithms in VMD, a popular molecular visualization and analysis tool. VMD (visual molecular dynamics) is a software system designed for displaying, animating, and analyzing large biomolecular systems. A motivation for using GPU acceleration in VMD is to make slow batch-mode jobs fast enough for interactive use, thereby drastically improving the productivity of scientific investigations. A molecular orbital (MO) represents a statistical state in which an electron can be found in a molecule, where the MO's spatial distribution is correlated with the associated electron's probability density. Visualization of MOs is an important task for understanding the chemistry of molecular systems. MOs appeal to the chemist's intuition, and inspection of the MOs aids in explaining chemical reactivities. The performance of each of the presented MO algorithms was evaluated on several hardware platforms. The test datasets were selected to be representative of the range of quantum chemistry simulation data that researchers often work with, and to exercise the limits of the algorithms, particularly in the case of the GPU. The development of a range-limited version of the molecular orbital algorithm that uses a distance cutoffto truncate the contributions of atoms that are either far away or that have very rapidly decaying exponential terms can change the molecular orbital computation from a quadratic time complexity algorithm into one with linear time complexity, enabling it to perform significantly faster for display of very large quantum chemistry simulations. © 2011
AB - This chapter presents several graphics processing unit (GPU) algorithms for evaluating molecular orbitals on three-dimensional lattices, as is commonly used for molecular visualization. The GPU kernels described here form the basis for the high-performance molecular orbital display algorithms in VMD, a popular molecular visualization and analysis tool. VMD (visual molecular dynamics) is a software system designed for displaying, animating, and analyzing large biomolecular systems. A motivation for using GPU acceleration in VMD is to make slow batch-mode jobs fast enough for interactive use, thereby drastically improving the productivity of scientific investigations. A molecular orbital (MO) represents a statistical state in which an electron can be found in a molecule, where the MO's spatial distribution is correlated with the associated electron's probability density. Visualization of MOs is an important task for understanding the chemistry of molecular systems. MOs appeal to the chemist's intuition, and inspection of the MOs aids in explaining chemical reactivities. The performance of each of the presented MO algorithms was evaluated on several hardware platforms. The test datasets were selected to be representative of the range of quantum chemistry simulation data that researchers often work with, and to exercise the limits of the algorithms, particularly in the case of the GPU. The development of a range-limited version of the molecular orbital algorithm that uses a distance cutoffto truncate the contributions of atoms that are either far away or that have very rapidly decaying exponential terms can change the molecular orbital computation from a quadratic time complexity algorithm into one with linear time complexity, enabling it to perform significantly faster for display of very large quantum chemistry simulations. © 2011
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U2 - 10.1016/B978-0-12-384988-5.00001-2
DO - 10.1016/B978-0-12-384988-5.00001-2
M3 - Chapter
AN - SCOPUS:84884457969
SN - 9780123849885
SP - 5
EP - 18
BT - GPU Computing Gems Emerald Edition
PB - Elsevier Inc.
ER -