Current trends in parallel processors call for the design of efficient massively parallel
algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of …

This work describes an implementation of canonical and Gibbs ensemble Monte Carlo
simulations on graphics processing units (GPUs). The pair-wise energy calculations, which …

We consider Monte Carlo simulations of classical spin models of statistical mechanics using
the massively parallel architecture provided by graphics processing units (GPUs). We …

The gold-standard definition of the Direct Simulation Monte Carlo (DSMC) method is given
in the 1994 book by Bird [Molecular Gas Dynamics and the Direct Simulation of Gas Flows …

Modern graphics processing units (GPUs) provide impressive computing resources, which
can be accessed conveniently through the CUDA programming interface. We describe how …

Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered
in condensed matter physics and statistical mechanics, this book provides an introduction to …

Applications that require substantial computational resources today cannot avoid the use of
heavily parallel machines. Embracing the opportunities of parallel computing and especially …

In order to run computer simulations efficiently on massively parallel computers with
hundreds of thousands or millions of processors, care must be taken that the calculation is …

We describe Janus, a massively parallel FPGA-based computer optimized for the simulation
of spin glasses, theoretical models for the behavior of glassy materials. FPGAs (as …

The compute unified device architecture (CUDA) is a programming approach for performing
scientific calculations on a graphics processing unit (GPU) as a data-parallel computing …