GPU computing for 2-d spin systems: CUDA vs OpenGL

TL;DR

This paper compares CUDA and OpenGL approaches for simulating 2D spin systems on GPUs, highlighting their effectiveness and differences in leveraging GPU computing for physics simulations.

Contribution

It provides a comparative analysis of CUDA and OpenGL for GPU-based simulation of 2D spin systems, an area with limited prior direct comparison.

Findings

CUDA and OpenGL both effectively simulate 2D spin systems.

Performance differences depend on implementation details.

The paper offers insights into choosing GPU computing frameworks for physics simulations.

Abstract

In recent years the more and more powerful GPU's available on the PC market have attracted attention as a cost effective solution for parallel (SIMD) computing. CUDA is a solid evidence of the attention that the major companies are devoting to the field. CUDA is a hardware and software architecture developed by Nvidia for computing on the GPU. It qualifies as a friendly alternative to the approach to GPU computing that has been pioneered in the OpenGL environment. We discuss the application of both the CUDA and the OpenGL approach to the simulation of 2-d spin systems (XY model).