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GPU-enabled simulation of fully atomistic macromolecular systems is rapidly gaining momentum, enabled by massive parallelism and the parallelizability of various components of the underlying algorithms and methodologies. Here, we consider key aspects required for obtaining realistic macromolecular systems specifically adapted to GPUs; these aspects include realistic mathematical models and valid simulations.
Recently, the Graphic Processor Unit (GPU) has evolved into a highly parallel, multithreaded, many-core processor with tremendous computational horsepower and very high memory bandwidth. To improve the simulation efficiency of complex flow phenomena in the field of computational fluid dynamics, a CUDA-based simulation algorithm of large eddy simulation using multiple GPUs is proposed. Our implementation...
Over the past five years, graphics processing units (GPUs) have had a transformational effect on numerical lattice quantum chromodynamics (LQCD) calculations in nuclear and particle physics. While GPUs have been applied with great success to the post-Monte Carlo “analysis” phase which accounts for a substantial fraction of the workload in a typical LQCD calculation, the initial Monte Carlo “gauge...
In this work, we focus on flow animation in elastic surfaces described by mass-spring models for computer game applications. We propose the combination of an efficient fluid model, that does not require solution of complicated equations, with a mass-spring approach to simulate the deformable surface. Firstly, we describe the fluid model for simulating the flow and its GPU implementation. The simulation...
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