Research and Analysis the Performance of NAMD- Molecular Dynamics Simulation Based Multi-core +GPU
Yang Zhang, Wen Bo Chen, Qi Feng Bai, Lian Li
Available Online March 2013.
- https://doi.org/10.2991/iccsee.2013.72How to use a DOI?
- GPU,NAMD,CUDA, molecular stimulation , Performance analyses, NVIDIA Tesla C2050
- Nowadays, the GPU can provide about one order of magnitude accelerated over CPU code and even more, so it can be used in large scale science computing applications. The paper based on NVIDIA Tesla C2050 and dual-core CPU server through use NAMD 2.9 simulates three differences molecule number proteins: Beta2- adrenergic receptor, SET9 and Ubiquitin. Through the comparison and analyses the results of the simulations experiment, we can conclusion that the difference systems of molecule will lead to the difference GPU accelerated. The computing times of four GPU is nearly half of the time used by 1 GPU; and this is especially true in the case of macromolecules. Furthermore, from the GPU’s memory utilization rate, the larger the protein system is, the higher the memory use of the GPU is. NVIDIA Tesla C2050 is can satisfy an even larger system simulation. The paper provides the best options for application of this software use the GPU and multi-core framework, a reference to building large scale molecule stimulations platforms, and a solution to science application of large molecule stimulation.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yang Zhang AU - Wen Bo Chen AU - Qi Feng Bai AU - Lian Li PY - 2013/03 DA - 2013/03 TI - Research and Analysis the Performance of NAMD- Molecular Dynamics Simulation Based Multi-core +GPU BT - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) PB - Atlantis Press SP - 280 EP - 283 SN - 1951-6851 UR - https://doi.org/10.2991/iccsee.2013.72 DO - https://doi.org/10.2991/iccsee.2013.72 ID - Zhang2013/03 ER -