Blue Matter, an application framework for molecular simulation on blue gene
Journal of Parallel and Distributed Computing - High-performance computational biology
GPGPU: general purpose computation on graphics hardware
ACM SIGGRAPH 2004 Course Notes
Parallel Programming in C with MPI and OpenMP
Parallel Programming in C with MPI and OpenMP
General purpose molecular dynamics simulations fully implemented on graphics processing units
Journal of Computational Physics
Program optimization carving for GPU computing
Journal of Parallel and Distributed Computing
Architecture-aware optimization targeting multithreaded stream computing
Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units
Fine-grain parallelism using multi-core, Cell/BE, and GPU Systems
Parallel Computing
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In this work, we present a first step towards the efficient implementation of polarizable molecular mechanics force fields with GPU acceleration. The computational bottleneck of such applications is found in the treatment of electrostatics, where higher-order multipoles and a self-consistent treatment of polarization effects are needed. We have coded these sections, for the case of a non-periodic simulation, with the CUDA programming model. Results show a speedup factor of 21 for a single precision GPU implementation, when comparing to the serial CPU version. A discussion of the optimization and parameterization steps is included. Comparison between different graphic cards and a shared memory parallel CPU implementation is also given. The current work demonstrates the potential usefulness of GPU programming in accelerating this field of applications.