Moleclar-dynamics simulations using spatial decomposition and task-based parallelism
Date
2016-05-30
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Abstract
Molecular Dynamics (MD) simulations are an integral method in the computational studies of
materials. This thesis discusses an algorithm for large-scale MD simulations using modern multiand
many-core systems on distributed computing networks. In order to utilize the full processing
power of these systems, algorithms must be updated to account for newer hardware, such as the
many-core Intel Xeon Phi co-processor.
The hybrid method is a data-parallel method of parallelization which combines spatial decomposition
using the Message Passing Interface (MPI) to distribute the system onto multiple nodes,
along with the cell-task method used for task based parallelism on each node. This allows for the
improved performance of task based parallelism on single compute nodes in addition to the benefit
of distributed computing allowed by MPI.
Results from benchmark simulations on Intel Xeon multi-core processors, and Intel Xeon Phi
coprocessors are presented. Results show that the hybrid method provides better performance
than either spatial decomposition or cell-task methods alone on single nodes, and that the hybrid
method outperforms the spatial decomposition method on multiple nodes, on a variety of system
configurations.
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Keywords
Molecular Dynamics (MD), simulations