Design and engineering of a simplified workflow execution for the MG5aMC event generator on GPUs and vector CPUs

TL;DR

This paper discusses reengineering the Madgraph5_aMC@NLO event generator to efficiently run on GPUs and vector CPUs, aiming to enhance performance for high energy physics data analysis at HPC centers.

Contribution

It introduces a new software architecture for the event generator to enable efficient GPU and vector CPU execution, modernizing and optimizing its performance.

Findings

Preliminary results show promising GPU acceleration.

Software architecture supports efficient parallel execution.

Ongoing development with future performance improvements.

Abstract

Physics event generators are essential components of the data analysis software chain of high energy physics experiments, and important consumers of their CPU resources. Improving the software performance of these packages on modern hardware architectures, such as those deployed at HPC centers, is essential in view of the upcoming HL-LHC physics programme. In this paper, we describe an ongoing activity to reengineer the Madgraph5_aMC@NLO physics event generator, primarily to port it and allow its efficient execution on GPUs, but also to modernize it and optimize its performance on vector CPUs. We describe the motivation, engineering process and software architecture design of our developments, as well as the current challenges and future directions for this project. This paper is based on our submission to vCHEP2021 in March 2021,complemented with a few preliminary results that we presented during the conference. Further details and updated results will be given in later publications.