An NLO-Matched Initial and Final State Parton Shower on a GPU

TL;DR

This paper introduces GAPS, a GPU-accelerated NLO-matched initial and final state parton shower generator, demonstrating comparable speed and energy efficiency to large CPU clusters for LHC Z production simulations.

Contribution

The paper presents version 2 of GAPS, a GPU-based Monte Carlo event generator capable of NLO matching for initial and final state emissions, with significant speed and energy efficiency improvements.

Findings

GAPS on GPU matches the speed of a 96-core CPU cluster.

GAPS reduces energy consumption compared to traditional CPU-based simulations.

GAPS efficiently simulates LHC Z production with NLO accuracy.

Abstract

Recent developments have demonstrated the potential for high simulation speeds and reduced energy consumption by porting Monte Carlo Event Generators to GPUs. We release version 2 of the CUDA C++ parton shower event generator GAPS, which can simulate initial and final state emissions on a GPU and is capable of hard-process matching. As before, we accompany the generator with a near-identical C++ generator to run simulations on single-core and multi-core CPUs. Using these programs, we simulate NLO Z production at the LHC and demonstrate that the speed and energy consumption of an NVIDIA V100 GPU are on par with a 96-core cluster composed of two Intel Xeon Gold 5220R Processors, providing a potential alternative to cluster computing.