G. Kosec^1,2, P. Zinterhof³

CMES-Computer Modeling in Engineering & Sciences, Vol.91, No.5, pp. 377-396, 2013, DOI:10.3970/cmes.2013.091.377

Abstract This paper deals with the implementation of the local meshless numerical method (LMM) on general purpose graphics processing units (GPU) in solving partial differential equations (PDE). The local meshless solution procedure is formulated in a way suitable for parallel execution and has been implemented on multiple GPUs. The implementation is tested on a solution of diffusion equation in a 2D domain. Different setups of the meshless approach regarding the selection of basis functions are tested on an interval up to 2.5 million of computational points. It is shown that monomials are a good selection of More >

Ji Joong Moon¹, Seung Jo Kim¹, Minhyung Lee²

CMES-Computer Modeling in Engineering & Sciences, Vol.59, No.3, pp. 275-300, 2010, DOI:10.3970/cmes.2010.059.275

Abstract This paper describes the parallelization of contact/impact simulation for fracture modeling of brittle materials using a node separation scheme (NSS). We successfully demonstrated the fracture modeling of brittle materials using a cohesive fracture model. Since a NSS continuously generates new free surfaces as the computation progresses, the methodology requires increased computational time. To perform a simulation within a reasonable time period, a parallelization study is conducted. Particular methods for effective parallelization, especially for brittle materials, are described in detail. The crucial and most difficult strategy is the management of the data structure and communication needed More >

Z. Bittnar¹, B. Patzák¹, D. Rypl¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.13, No.3, pp. 55-56, 2009, DOI:10.3970/icces.2009.013.055

Abstract This paper deals with the design of framework for adaptive FEM analysis with dynamic load balancing in nondedicated parallel cluster computing environments. It describes in detail the structure and design of individual components of the framework.
The application of adaptivity paradigm to engineering problems results in computationally very demanding analysis in terms of both computational time and computer resources (memory, disk space, etc.). These demands can be alleviated by performing the analysis in a parallel computing environment. Typical parallel application decreases the demands on memory and other resources by spreading the task over several mutually… More >

Tae-Hyuk Ahn¹, Layne T. Watson^1,2, Yang Cao^1,1, Clifford A. Shaffer¹, William T. Baumann³

CMES-Computer Modeling in Engineering & Sciences, Vol.51, No.1, pp. 27-52, 2009, DOI:10.3970/cmes.2009.051.027

Abstract For biochemical systems, where some chemical species are represented by small numbers of molecules, discrete and stochastic approaches are more appropriate than continuous and deterministic approaches. The continuous deterministic approach using ordinary differential equations is adequate for understanding the average behavior of cells, while the discrete stochastic approach accurately captures noisy events in the growth-division cycle. Since the emergence of the stochastic simulation algorithm (SSA) by Gillespie, alternative algorithms have been developed whose goal is to improve the computational efficiency of the SSA. This paper explains and empirically compares the performance of some of these More >