Abstract

In Parallel programming, a programmer needs to understand hardware environment, programming paradigm and primitives available in the programming language. Most of the time, parallel programmes are written for a specific architecture and cannot typically adapt to other architectures Particularly, programs written for shared memory architectures are unsuitable for distributed or hybrid architectures. This paper proposes Adaptive Design Pattern for Parallel Programming to improve adaptability, flexibility with achieving performance on different architectures. Molecular Dynamics (MD) simulation is required to scale to various architectures from simple machine to cluster of workstations. In this study, MD Simulation experimented using both pure benchmark code and code based on adaptive design patterns. Redesigned MD Simulation with Adaptive Design Pattern claims parallel efficiency from 56% to 90% for different number of processing elements used. The solution demonstrates adaptability to different architectures and scalability to use with large number of atoms and long duration simulation.

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