Computer Physics Communications, 216, 95–101(2017).
Yachong Guo, Vladimir A. Baulin
We present parallel version of Rosenbluth Self-Avoiding Walk generation method implemented on Graphics Processing Units (GPUs) using CUDA libraries. The method scales almost linearly with the number of CUDA cores and the method efficiency has only hardware limitations. The method is introduced in two realizations: on a cubic lattice and in real space. We find a good agreement between serial and parallel implementations and consistent results between lattice and real space realizations of the method for linear chain statistics. The developed GPU implementations of Rosenbluth algorithm can be used in Monte Carlo simulations and other computational methods that require large sampling of molecules conformations.
Latest posts by Vladimir Baulin (see all)
- The Effect of Coatings and Nerve Growth Factor on Attachment and Differentiation of Pheochromocytoma Cells - 31/12/2017
- Understanding the interactions between sebum triglycerides and water: a molecular dynamics simulation study - 14/12/2017
- Reduction of the relative centrifugal force influences cell number and growth factor release within injectable PRF-based matrices - 02/11/2017