High performance implementations of the 2D Ising model on GPUs

Published: 16 Jul 2020 | Version 1 | DOI: 10.17632/xrb9xtkbcp.1

Description of this data

We present and make available novel implementations of the two-dimensional Ising model that is used as a benchmark to show the computational capabilities of modern Graphic Processing Units (GPUs). The rich programming environment now available on GPUs and flexible hardware capabilities allowed us to quickly experiment with several implementation ideas: a simple stencil-based algorithm, recasting the stencil operations into matrix multiplies to take advantage of Tensor Cores available on NVIDIA GPUs, and a highly optimized multi-spin coding approach. Using the managed memory API available in CUDA allows for simple and efficient distribution of these implementations across a multi-GPU NVIDIA DGX-2 server. We show that even a basic GPU implementation can outperform current results published on TPUs (Yang et al., 2019) and that the optimized multi-GPU implementation can simulate very large lattices faster than custom FPGA solutions (Ortega-Zamorano et al., 2016).

Experiment data files

This data is associated with the following publication:

High performance implementations of the 2D Ising model on GPUs

Published in: Computer Physics Communications

Latest version

  • Version 1


    Published: 2020-07-16

    DOI: 10.17632/xrb9xtkbcp.1

    Cite this dataset

    Romero, Joshua; Bisson, Mauro; Fatica, Massimiliano; Bernaschi, Massimo (2020), “High performance implementations of the 2D Ising model on GPUs”, Mendeley Data, v1 http://dx.doi.org/10.17632/xrb9xtkbcp.1


Views: 36
Downloads: 0


Statistical Physics, Thermodynamics, Computational Physics


MIT Learn more

The files associated with this dataset are licensed under a MIT License licence.

What does this mean?
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.