Sampling rare events in hybrid statistical physics quantum mechanical studies of hydrophobic interactions in liquids: A gpu implementation
Date Issued
2015
Author(s)
Pejov, Ljupčo
Djinevski, Leonid
Abstract
A method for sampling rare events throughout hybrid statistical physics quantum mechanical studies of hydrophobic interactions in liquid phases was
analyzed and implemented on GPU architecture. The rare events considered in
the present case are related to formation of the so-called dangling X-H bonds of
small polar solvent molecules around notably non-polar solute molecules. The
approach is based on detecting various populations of polar solvent molecules
which reside in the first solvation shell around the non-polar solute and noting
the differences between such populations. In particular, the search for structurally
different populations of solvent molecules around the solute is started by detecting the differences in vibrational spectroscopic characteristics of the X-H stretching frequencies, which could be computed by various approaches, such as, e.g.
within the Stark shift approximation. The results show x25 overall speedup of the
GPU implementation compared to the sequential implementation.
analyzed and implemented on GPU architecture. The rare events considered in
the present case are related to formation of the so-called dangling X-H bonds of
small polar solvent molecules around notably non-polar solute molecules. The
approach is based on detecting various populations of polar solvent molecules
which reside in the first solvation shell around the non-polar solute and noting
the differences between such populations. In particular, the search for structurally
different populations of solvent molecules around the solute is started by detecting the differences in vibrational spectroscopic characteristics of the X-H stretching frequencies, which could be computed by various approaches, such as, e.g.
within the Stark shift approximation. The results show x25 overall speedup of the
GPU implementation compared to the sequential implementation.
Subjects
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