cuLGT: Lattice Gauge Fixing on GPUs

TL;DR

This paper presents an optimized GPU implementation for lattice gauge fixing in SU(3) and SU(2) theories, achieving high performance and improved usability for large-scale simulations.

Contribution

The authors develop an enhanced CUDA-based code for gauge fixing that significantly increases performance and ease of integration compared to previous versions.

Findings

Achieves up to 470 GFlops on GTX 580 GPU.

Uses 4 or 8 threads per lattice site for parallelism.

Improves performance and usability of gauge fixing code.

Abstract

We adopt CUDA-capable Graphic Processing Units (GPUs) for Landau, Coulomb and maximally Abelian gauge fixing in 3+1 dimensional SU(3) and SU(2) lattice gauge field theories. A combination of simulated annealing and overrelaxation is used to aim for the global maximum of the gauge functional. We use a fine grained degree of parallelism to achieve the maximum performance: instead of the common 1 thread per site strategy we use 4 or 8 threads per lattice site. Here, we report on an improved version of our publicly available code (www.cuLGT.com and github.com/culgt) which again increases performance and is much easier to include in existing code. On the GeForce GTX 580 we achieve up to 470 GFlops (utilizing 80% of the theoretical peak bandwidth) for the Landau overrelaxation code.