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Solving Lattice QCD systems of equations using mixed precision solvers on GPUs

10 Pith papers cite this work. Polarity classification is still indexing.

10 Pith papers citing it
abstract

Modern graphics hardware is designed for highly parallel numerical tasks and promises significant cost and performance benefits for many scientific applications. One such application is lattice quantum chromodyamics (lattice QCD), where the main computational challenge is to efficiently solve the discretized Dirac equation in the presence of an SU(3) gauge field. Using NVIDIA's CUDA platform we have implemented a Wilson-Dirac sparse matrix-vector product that performs at up to 40 Gflops, 135 Gflops and 212 Gflops for double, single and half precision respectively on NVIDIA's GeForce GTX 280 GPU. We have developed a new mixed precision approach for Krylov solvers using reliable updates which allows for full double precision accuracy while using only single or half precision arithmetic for the bulk of the computation. The resulting BiCGstab and CG solvers run in excess of 100 Gflops and, in terms of iterations until convergence, perform better than the usual defect-correction approach for mixed precision.

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hep-lat 10

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2026 7 2025 3

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representative citing papers

The Lambda 1405 at the $SU(3)$ point in lattice QCD

hep-lat · 2026-02-23 · unverdicted · novelty 7.0

Lattice QCD at the SU(3) symmetric point extracts energy levels for singlet and octet baryon-meson channels to inform the two-pole structure of Lambda(1405).

Inverse problem in the LaMET framework

hep-lat · 2025-04-24 · unverdicted · novelty 5.0

Analysis of non-perturbative lattice data shows that the inverse problem in LaMET introduces significant uncertainties in parton distributions, especially from harmonics around λ=5-15, and that exact asymptotic decay matters little in the currently applicable x range.

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