Towards Lattice QCD+QED Simulations on GPUs

Abstract

Improving the precision in particle physics predictions obtained from lattice simulations of quantum chromodynamics (QCD) requires extension of the interactions considered thus far, leading to additional computational demands. Most commonly used publicly available program packages for efficient simulations of Wilson discretization of the Dirac operator are highly scalable on CPU hardware. In order to be able to run efficiently on existing and upcoming hybrid architectures, one needs to rethink the current strategy for data types used at different stages of the simulation, most notably in frequent solves of the Dirac equation. We perform the first steps towards porting on GPUs of the three type of solvers used in the simulations of clover improved Wilson fermions: Conjugate Gradient, Schwarz preconditioned GCR solver, and a variant of the deflated solver. The analysis of the reduced precision data types' impact on the convergence of each solver indicates several possibilities for overall performance improvement.