A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation
The Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational structural biology to estimate the electrostatic energetic component of the assembly of molecular biologica...
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Online Access: | http://dx.doi.org/10.1155/2014/560987 |
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doaj-4ed9dd0797ed4e1bb529123ca67d729b2020-11-24T23:22:40ZengHindawi LimitedBioMed Research International2314-61332314-61412014-01-01201410.1155/2014/560987560987A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann EquationJosé Colmenares0Antonella Galizia1Jesús Ortiz2Andrea Clematis3Walter Rocchia4Drug Discovery and Development, Italian Institute of Technology, 16163 Genova, ItalyIMATI, CNR, 16149 Genova, ItalyDepartment of Advanced Robotics, Italian Institute of Technology, 16163 Genova, ItalyIMATI, CNR, 16149 Genova, ItalyDrug Discovery and Development, Italian Institute of Technology, 16163 Genova, ItalyThe Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational structural biology to estimate the electrostatic energetic component of the assembly of molecular biological systems. In the last decades, the amount of data concerning proteins and other biological macromolecules has remarkably increased. To fruitfully exploit these data, a huge computational power is needed as well as software tools capable of exploiting it. It is therefore necessary to move towards high performance computing and to develop proper parallel implementations of already existing and of novel algorithms. Nowadays, workstations can provide an amazing computational power: up to 10 TFLOPS on a single machine equipped with multiple CPUs and accelerators such as Intel Xeon Phi or GPU devices. The actual obstacle to the full exploitation of modern heterogeneous resources is efficient parallel coding and porting of software on such architectures. In this paper, we propose the implementation of a full Poisson-Boltzmann solver based on a finite-difference scheme using different and combined parallel schemes and in particular a mixed MPI-CUDA implementation. Results show great speedups when using the two schemes, achieving an 18.9x speedup using three GPUs.http://dx.doi.org/10.1155/2014/560987 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
José Colmenares Antonella Galizia Jesús Ortiz Andrea Clematis Walter Rocchia |
spellingShingle |
José Colmenares Antonella Galizia Jesús Ortiz Andrea Clematis Walter Rocchia A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation BioMed Research International |
author_facet |
José Colmenares Antonella Galizia Jesús Ortiz Andrea Clematis Walter Rocchia |
author_sort |
José Colmenares |
title |
A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation |
title_short |
A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation |
title_full |
A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation |
title_fullStr |
A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation |
title_full_unstemmed |
A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation |
title_sort |
combined mpi-cuda parallel solution of linear and nonlinear poisson-boltzmann equation |
publisher |
Hindawi Limited |
series |
BioMed Research International |
issn |
2314-6133 2314-6141 |
publishDate |
2014-01-01 |
description |
The Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational structural biology to estimate the electrostatic energetic component of the assembly of molecular biological systems. In the last decades, the amount of data concerning proteins and other biological macromolecules has remarkably increased. To fruitfully exploit these data, a huge computational power is needed as well as software tools capable of exploiting it. It is therefore necessary to move towards high performance computing and to develop proper parallel implementations of already existing and of novel algorithms. Nowadays, workstations can provide an amazing computational power: up to 10 TFLOPS on a single machine equipped with multiple CPUs and accelerators such as Intel Xeon Phi or GPU devices. The actual obstacle to the full exploitation of modern heterogeneous resources is efficient parallel coding and porting of software on such architectures. In this paper, we propose the implementation of a full Poisson-Boltzmann solver based on a finite-difference scheme using different and combined parallel schemes and in particular a mixed MPI-CUDA implementation. Results show great speedups when using the two schemes, achieving an 18.9x speedup using three GPUs. |
url |
http://dx.doi.org/10.1155/2014/560987 |
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