Accelerating Cell Dynamics Simulations of Soft Materials using CUDA-GPU

Abstract

Soft materials are a highly demanded class of research for predicting the characteristics of phase separation and self-assembly into nanoscale structures. One of the most well-known methods to demonstrate and simulate dynamic behavior of particles, such as particle tracking, and to consider different effects of simulation parameters is cell dynamic simulation. In fact, cell dynamic simulation as a cellular computerization can be used to investigate different aspects of morphological topographies of soft material system. To achieve accurate and efficient computational results for cell dynamic simulation method, two factors are essential and vital: first, computing/calculating time-scale; and second, simulation system size. Consequently, finding available computing algorithms and resources such as sequential algorithm for implementing a complex technique and achieving precise results is critical and expensive. Therefore, it is very important to consider a parallel algorithm and programming model to solve time-consuming and massive computational processing. This paper presents a novel GPU-based parallel acceleration approach to cell dynamics simulations (CDS) for a spherical phase diblock copolymer under a shear flow. A new achievement is based on a commodity NVIDIA Quadro K5000 graphic card and Compute Unified Device Architecture (CUDA) C language.