Title :
Accelerating Dynamics Simulation of Solidification Processes of Liquid Metals Using GPU with CUDA
Author :
Jie Liang ; Kenli Li ; Lin Shi ; Yingqiang Liao
Author_Institution :
Sch. of Inf. Sci. & Eng., Hunan Univ., Changsha, China
Abstract :
Molecular dynamics simulation is a powerful tool to simulate and analyze complex physical processes and phenomena at atomic characteristic for predicting the natural time-evolution of a system of atoms. Precise simulation of processes such as liquid metal solidification processes simulation has strong requirements both in the simulation size and computing timescale. Therefore, finding available computing resources is crucial to accelerate computation of solidification processes simulations. This paper presents a new approach to accelerate calculation of liquid metal solidification processes based on the previous study implemented on the CPU clusters, where the GPU-based MD (molecular dynamics) algorithm using a fine-grained spatial decomposition method enlarge the scale of the simulation system to a simulation system involving 10, 000, 000 atoms. The algorithms are implemented using FORTRAN and CUDA on a commodity NVIDIA Tesla M2050 card, where experimental results demonstrate that GPU-based calculations are typically 9~11 times faster than the corresponding sequential execution and approximately 1.5~2 times faster than 16-CPU clusters implementations.
Keywords :
FORTRAN; graphics processing units; liquid metals; materials science computing; parallel architectures; solidification; CUDA; FORTRAN; GPU-based MD algorithm; atomic characteristic; commodity NVIDIA Tesla M2050 card; fine-grained spatial decomposition; liquid metal; molecular dynamics simulation; natural time-evolution; solidification process; Computational modeling; Computer architecture; Force; Graphics processing units; Instruction sets; Microprocessors; Graphics processing unit; Molecular dynamics; cell division; solidification process;
Conference_Titel :
Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2013 IEEE 27th International
Conference_Location :
Cambridge, MA
Print_ISBN :
978-0-7695-4979-8
DOI :
10.1109/IPDPSW.2013.84