Showing papers by "Rezaul Chowdhury published in 2012"
10 Nov 2012
TL;DR: An octree-based hierarchical algorithm, built on GreengardRokhlin type near and far decomposition of data points which calculates the polarization energy of a molecule using the r6 approximation of Generalized Born (GB) Radii of atoms
Abstract: When a molecule experiences an electric field, its charge distribution is relaxed in response to that field. The energy associated with this relaxation is known as the polarization energy . Computing the polarization energy between a ligand (i.e., a small molecule such as a drug molecule) and a receptor (e.g., a virus molecule) is of utmost importance in drug design, protein-protein docking, virus/bacterium cell analysis, molecular dynamics simulations for determining the molecular conformation with minimal total free energy. We have implemented distributed-memory and distributed shared-memory parallel algorithms for approximating polarization energy of a molecule by extending a prior work for shared-memory (multicore) architectures. This is an octree-based hierarchical algorithm, built on GreengardRokhlin type near and far decomposition of data points (i.e., atoms and points sampled from the molecular surface) which calculates the polarization energy of a molecule using the r6 approximation of Generalized Born (GB) Radii of atoms. Both Poisson-Boltzmann (PB) GeneralizedBorn (GB) models can be used for approximating polarization energy. However, due to high computational costs PB method is rarely used for large molecules such as proteins.
10 Nov 2012
TL;DR: This work has implemented distributed-memory and distributed-shared-memory parallel octree based algorithms for approximating polarization energy of protein molecules by extending prior work of Chowdhury et al. (2010) for shared-memory architectures and shown that their implementations outperform state-of-the-art polarization energy implementations available in Amber-12, Gromacs-5.4.3, Tinker-6.0 and GBr6.3.
Abstract: We have implemented distributed-memory and distributed-shared-memory parallel octree based algorithms for approximating polarization energy of protein molecules by extending prior work of Chowdhury et al. (2010) for shared-memory architectures. This is an octree-based hierarchical algorithm, built on Greengard-Rokhlin type near and far decomposition of data points (i.e., atoms and points sampled from the molecular surface) which calculates the polarization energy of protein molecules using the r^6 approximation of Generalized Born radii of atoms. We have shown that our implementations outperform state-of-the-art polarization energy implementations available in Amber-12, Gromacs-5.4.3, Tinker-6.0 and GBr6. Using approximations and efficient load-balancing scheme, we have achieved a speedup factor of about 34k w.r.t. the naive exact algorithm with less than 1% error using as few as 144 cores (i.e., 12 compute nodes with 12 cores each) for molecules with half a million of atoms.
04 Jun 2012
TL;DR: This paper introduces the kissing problem: given a rectangular room with n people in it, what is the most efficient way for each pair of people to kiss each other goodbye?
Abstract: This paper introduces the kissing problem: given a rectangular room with n people in it, what is the most efficient way for each pair of people to kiss each other goodbye? The room is viewed as a set of pixels that form a subset of the integer grid. At most one person can stand on a pixel at once, and people move horizontally or vertically. In order to move into a pixel in time step t, the pixel must be empty in time step t−1.
The paper gives one algorithm for kissing everyone goodbye.
(1) This algorithm is a 4 + o(1)-approximation algorithm in a crowded room (e.g., only one unoccupied pixel).
(2) It is a 10 + o(1)-approximation algorithm for kissing in a comfortable room (e.g., at most half the pixels are empty).
(3) It is a 25+o(1)-approximation for kissing in a sparse room.