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Related papers: Parallel Tempering Simulation of the three-dimensi…

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Monte Carlo simulation techniques, like simulated annealing and parallel tempering, are often used to evaluate low-temperature properties and find ground states of disordered systems. Here we compare these methods using direct calculations…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. J. Moreno , H. G. Katzgraber , Alexander K. Hartmann

This paper describes an algorithm for selecting parameter values (e.g. temperature values) at which to measure equilibrium properties with Parallel Tempering Monte Carlo simulation. Simple approaches to choosing parameter values can lead to…

Other Condensed Matter · Physics 2015-05-18 Firas Hamze , Neil Dickson , Kamran Karimi

We present several efficient implementations of the simulated annealing algorithm for Ising spin glasses on sparse graphs. In particular, we provide a generic code for any choice of couplings, an optimized code for bipartite graphs, and…

Disordered Systems and Neural Networks · Physics 2015-09-25 S. V. Isakov , I. N. Zintchenko , T. F. Rønnow , M. Troyer

We develop a parallel rejection algorithm to tackle the problem of low acceptance in Monte Carlo methods, and apply it to the simulation of the hopping conduction in Coulomb glasses using Graphics Processing Units, for which we also…

Disordered Systems and Neural Networks · Physics 2014-08-19 Ezequiel E. Ferrero , Alejandro B. Kolton , Matteo Palassini

Large-scale deep learning benefits from an emerging class of AI accelerators. Some of these accelerators' designs are general enough for compute-intensive applications beyond AI and Cloud TPU is one such example. In this paper, we…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-19 Kun Yang , Yi-Fan Chen , Georgios Roumpos , Chris Colby , John Anderson

Population annealing is a Monte Carlo algorithm that marries features from simulated annealing and parallel tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a…

Disordered Systems and Neural Networks · Physics 2015-07-08 Wenlong Wang , Jonathan Machta , Helmut G. Katzgraber

Population annealing is a promising recent approach for Monte Carlo simulations in statistical physics, in particular for the simulation of systems with complex free-energy landscapes. It is a hybrid method, combining importance sampling…

Computational Physics · Physics 2017-09-14 Lev Yu. Barash , Martin Weigel , Michal Borovský , Wolfhard Janke , Lev N. Shchur

Differentiable model predictive control (MPC) offers a powerful framework for combining learning and control. However, its adoption has been limited by the inherently sequential nature of traditional optimization algorithms, which are…

Optimization and Control · Mathematics 2025-10-08 Emre Adabag , Marcus Greiff , John Subosits , Thomas Lew

The strategy of using CUDA-compatible GPUs as a parallel computation solution to improve the performance of programs has been more and more widely approved during the last two years since the CUDA platform was released. Its benefit extends…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-01-12 Chang Xu , Steven R. Kirk , Samantha Jenkins

Micro-macro models provide a powerful tool to study the relationship between microscale mechanisms and emergent macroscopic behavior. However, the detailed microscopic modeling may require tracking and evolving a high-dimensional…

Computational Physics · Physics 2019-08-13 Steven Cook , Tamar Shinar

We present a massive equilibrium simulation of the three-dimensional Ising spin glass at low temperatures. The Janus special-purpose computer has allowed us to equilibrate, using parallel tempering, L=32 lattices down to T=0.64 Tc. We…

We review a scalable two- and three-dimensional computer code for low-temperature plasma simulations in multi-material complex geometries. Our approach is based on embedded boundary (EB) finite volume discretizations of the minimal…

Computational Physics · Physics 2019-05-01 Robert Marskar

Restricted solid on solid surface growth models can be mapped onto binary lattice gases. We show that efficient simulation algorithms can be realized on GPUs either by CUDA or by OpenCL programming. We consider a deposition/evaporation…

Computational Physics · Physics 2015-03-17 Henrik Schulz , Géza Ódor , Gergely Ódor , Máté Ferenc Nagy

An existing hybrid MPI-OpenMP scheme is augmented with a CUDA-based fine grain parallelization approach for multidimensional distributed Fourier transforms, in a well-characterized pseudospectral fluid turbulence code. Basics of the hybrid…

Computational Physics · Physics 2018-08-07 Duane Rosenberg , Pablo D. Mininni , Raghu Reddy , Annick Pouquet

Markov Chain Monte Carlo (MCMC) underlies both statistical physics and combinatorial optimization, but mixes slowly near critical points and in rough landscapes. Parallel Tempering (PT) improves mixing by swapping replicas across…

Machine Learning · Computer Science 2025-09-30 Saleh Bunaiyan , Corentin Delacour , Shuvro Chowdhury , Kyle Lee , Kerem Y. Camsari

A two-dimensional Ising model with nearest-neighbors ferromagnetic interactions is implemented in a Field Programmable Gate Array (FPGA) board.Extensive Monte Carlo simulations were carried out using an efficient hardware representation of…

Hardware Architecture · Computer Science 2016-02-10 Francisco Ortega-Zamorano , Marcelo A. Montemurro , Sergio A. Cannas , José M. Jerez , Leonardo Franco

We apply a set of machine-learning (ML) techniques for the global exploration of the phase diagrams of two frustrated 2D Ising models with competing interactions. Based on raw Monte Carlo spin configurations generated for random system…

Statistical Mechanics · Physics 2021-12-03 Danilo Rodrigues de Assis Elias , Enzo Granato , Maurice de Koning

In this paper I report results for simulations of the three-dimensional gauge glass and the four-dimensional XY spin glass using the parallel tempering Monte Carlo method at low temperatures for moderate sizes. The results are qualitatively…

Disordered Systems and Neural Networks · Physics 2009-11-07 Helmut G. Katzgraber

We created an efficient algorithm suitable for graphics processing units (GPUs) to perform Monte Carlo simulations of a subset of reaction-diffusion models. The algorithm uses techniques that are specific to GPU programming, and combines…

Computational Physics · Physics 2013-03-06 R. D. Schram

Path integral Monte Carlo (PIMC) and path integral molecular dynamics (PIMD) provide the golden standard for the ab initio simulations of identical particles. In this work, we achieved significant GPU acceleration based on PIMD, which is…

Computational Physics · Physics 2026-03-31 Yunuo Xiong