We implemented a GPU-based parallel code to perform Monte Carlo simulations of the two-dimensional q-state Potts model. The algorithm is based on a checkerboard update scheme and assigns independent random number generators to each thread. The implementation allows to simulate systems up to ~109 spins with an average time per spin flip of 0.147 ns on the fastest GPU card tested, representing a speedup up to 155×, compared with an optimized serial code running on a high-end CPU. The possibility of performing high speed simulations at large enough system sizes allowed us to provide a positive numerical evidence about the existence of metastability on very large systems based on Binder’s criterion [1], namely, on the existence or not of specif...
We implement Monte Carlo algorithms for the simulation of spin-glass systems and optimize our codes ...
We optimize codes implementing Monte Carlo simulations of spin-glass systems for some multi-core CPU...
AbstractWe investigate new programming techniques for parallel tempering Monte Carlo simulations of ...
AbstractWe consider Monte Carlo simulations of classical spin models of statistical mechanics using ...
Monte Carlo simulations of the Ising model play an important role in the field of computational stat...
Graphics processing units (GPUs) are recently being used to an increasing degree for general computa...
Population annealing is a promising recent approach for Monte Carlo simulations in statistical physi...
The compute unified device architecture (CUDA) is a programming approach for performing scientific c...
We present a case study on the utility of graphics cards to perform massively parallel simulation of...
Simulations of systems with quenched disorder are extremely demanding, suffering from the combined e...
We discuss the advantages of parallelization by multithreading on graphics processing units (GPUs) f...
We present a case-study on the utility of graphics cards to perform massively parallel simulation of...
Abstract: Lattice spin models are useful for studying critical phenomena and allow the extraction of...
Data-parallel accelerator devices such as Graphical Processing Units (GPUs) are providing dramatic p...
We present a case-study on the utility of graphics cards to perform massively parallel sim ulation w...
We implement Monte Carlo algorithms for the simulation of spin-glass systems and optimize our codes ...
We optimize codes implementing Monte Carlo simulations of spin-glass systems for some multi-core CPU...
AbstractWe investigate new programming techniques for parallel tempering Monte Carlo simulations of ...
AbstractWe consider Monte Carlo simulations of classical spin models of statistical mechanics using ...
Monte Carlo simulations of the Ising model play an important role in the field of computational stat...
Graphics processing units (GPUs) are recently being used to an increasing degree for general computa...
Population annealing is a promising recent approach for Monte Carlo simulations in statistical physi...
The compute unified device architecture (CUDA) is a programming approach for performing scientific c...
We present a case study on the utility of graphics cards to perform massively parallel simulation of...
Simulations of systems with quenched disorder are extremely demanding, suffering from the combined e...
We discuss the advantages of parallelization by multithreading on graphics processing units (GPUs) f...
We present a case-study on the utility of graphics cards to perform massively parallel simulation of...
Abstract: Lattice spin models are useful for studying critical phenomena and allow the extraction of...
Data-parallel accelerator devices such as Graphical Processing Units (GPUs) are providing dramatic p...
We present a case-study on the utility of graphics cards to perform massively parallel sim ulation w...
We implement Monte Carlo algorithms for the simulation of spin-glass systems and optimize our codes ...
We optimize codes implementing Monte Carlo simulations of spin-glass systems for some multi-core CPU...
AbstractWe investigate new programming techniques for parallel tempering Monte Carlo simulations of ...