Parallelization and implementation of multi-spin Monte Carlo simulation of 2D square Ising model using MPI and C++
arXiv:1811.04384 · doi:10.1007/s40094-018-0301-4
Abstract
In this paper, we present a parallel algorithm for Monte Carlo simulation of the 2D Ising Model to perform efficiently on a cluster computer using MPI. We use C++ programming language to implement the algorithm. In our algorithm, every process creates a sub-lattice and the energy is calculated after each Monte Carlo iteration. Each process communicates with its two neighbor processes during the job and they exchange the boundary spin variables. Finally, the total energy of lattice is calculated by map-reduce method versus the temperature. We use multi-spin coding technique to reduce the interprocess communications. This algorithm has been designed in a way that an appropriate load-balancing exists and it benefits a good scalability. It has been executed on the cluster computer of Plasma Physics Research Center which includes 9 nodes and each node consists of two quad-core CPUs. Our results show that this algorithm is more efficient for large lattices and more iterations.
References in corpus (7)
- Multi-GPU Accelerated Multi-Spin Monte Carlo Simulations of the 2D Ising Model
- Simulating spin models on GPU
- GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional classical spin systems
- GPU-based single-cluster algorithm for the simulation of the Ising model
- CUDA programs for GPU computing of Swendsen-Wang multi-cluster spin flip algorithm: 2D and 3D Ising, Potts, and XY models
- Parallel Higher-order Boundary Integral Electrostatics Computation on Molecular Surfaces with Curved Triangulation
- Parallelization of an implicit algorithm for multi-dimensional particle-in-cell simulations