## Abstract We present a method of parallelizing flat histogram Monte Carlo simulations, which give the free energy of a molecular system as an output. In the serial version, a constant probability distribution, as a function of any system parameter, is calculated by updating an external potential
Parallelization strategies for molecular simulation using the Monte Carlo algorithm
โ Scribed by Douglas M. Jones; Julia M. Goodfellow
- Publisher
- John Wiley and Sons
- Year
- 1993
- Tongue
- English
- Weight
- 1012 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0192-8651
No coin nor oath required. For personal study only.
โฆ Synopsis
We describe the development of Metropolis Monte Carlo algorithms for a general network of multiple instruction multiple data (MIMD) parallel processors. The implementation of farm, event, and systolic parallel algorithms on transputer-based computers is detailed and their relative performance discussed. Although the emphasis is on methodology, the application of such parallel algorithms will be important for addressing computational problems such as the determination of free energy differences in complex biologically important molecular systems.
๐ SIMILAR VOLUMES
The accuracy and computational cost of a direct simulation Monte Carlo simulation are directly related to the number of particles per cell. Optimal computational efficiency is achieved when the minimum number of particles needed for accurate resolution is used in each cell. Particle count is shown t
A hybrid conformational search algorithm (DMC) is described that combines a modified form of molecular dynamics with Metropolis Monte Carlo sampling, using the COSMIC(9O) force field. Trial configurations are generated by short bursts of high-temperature dynamics in which the initial kinetic energy