Accelerating solidification process simulation for large-sized system of liquid metal atoms using GPU with CUDA
Journal Article
·
· Journal of Computational Physics
- School of Information Science and Engineering, Hunan University, Changshang, 410082 (China)
- School of Physics and Micro Electronic, Hunan University, Changshang, 410082 (China)
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 physical processes has strong requirements both in the simulation size and computing timescale. Therefore, finding available computing resources is crucial to accelerate computation. However, a tremendous computational resource (GPGPU) are recently being utilized for general purpose computing due to its high performance of floating-point arithmetic operation, wide memory bandwidth and enhanced programmability. As for the most time-consuming component in MD simulation calculation during the case of studying liquid metal solidification processes, this paper presents a fine-grained spatial decomposition method to accelerate the computation of update of neighbor lists and interaction force calculation by take advantage of modern graphics processors units (GPU), enlarging the scale of the simulation system to a simulation system involving 10 000 000 atoms. In addition, a number of evaluations and tests, ranging from executions on different precision enabled-CUDA versions, over various types of GPU (NVIDIA 480GTX, 580GTX and M2050) to CPU clusters with different number of CPU cores are discussed. The 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 cores clusters implementations. On the basis of the simulated results, the comparisons between the theoretical results and the experimental ones are executed, and the good agreement between the two and more complete and larger cluster structures in the actual macroscopic materials are observed. Moreover, different nucleation and evolution mechanism of nano-clusters and nano-crystals formed in the processes of metal solidification is observed with large-sized system.
- OSTI ID:
- 22230847
- Journal Information:
- Journal of Computational Physics, Journal Name: Journal of Computational Physics Journal Issue: Part A Vol. 257; ISSN JCTPAH; ISSN 0021-9991
- Country of Publication:
- United States
- Language:
- English
Similar Records
GPU-acceleration of tensor renormalization with PyTorch using CUDA
Accelerating Neutrino Event Generation in MARLEY Using CUDA-Based RNG and GPU Parallelization
A Monte Carlo neutron transport code for eigenvalue calculations on a dual-GPU system and CUDA environment
Journal Article
·
Wed Sep 20 20:00:00 EDT 2023
· Computer Physics Communications
·
OSTI ID:2202811
Accelerating Neutrino Event Generation in MARLEY Using CUDA-Based RNG and GPU Parallelization
Conference
·
Mon Jul 28 00:00:00 EDT 2025
· No journal information
·
OSTI ID:2574870
A Monte Carlo neutron transport code for eigenvalue calculations on a dual-GPU system and CUDA environment
Conference
·
Sun Jul 01 00:00:00 EDT 2012
·
OSTI ID:22105653