Watts per event: evaluating Sustainability of HEP Event Generators beyond the LHC era
For high-energy physics researchers, this work addresses the computational sustainability of event generators, though it is an incremental optimization of existing methods.
The study evaluates the sustainability of Monte Carlo event generators by benchmarking HIJING++ with a containerized toolset, showing that optimizing multithreading can reduce energy costs. The approach can lower the energy footprint of high-energy physics event generators.
The development, tuning and operation of Monte Carlo event generators beyond the LHC era require vast amount of resources. In this study we investigate the sustainability of these software with a containerized set of tools (named 77rev/propripy), by benchmarking the HIJING++ heavy-ion Monte Carlo event generator. We analyze the performance of various CPU architectures and show that by choosing the level of multithreading properly, the cost of event generation can be optimized. The presented approach can reduce the energy footprint of high-energy physics event generators and therefore alleviate the ever-increasing, ubiquitous computational challenges.