Benchmarking the HERWIG Event Generator in High-Throughput Computing Infrastructure

This study presents a methodology to profile the energy consumption and CO2e emissions of High Energy Physics (HEP) software using Intel’s RAPL interface on a High-Throughput Computing (HTC) cluster. Power measurements from RAPL were compared with the plug-based Prometheus and Green Algorithms calculator. The methodology was applied to benchmark HERWIG 7.3 for Drell–Yan processes [1] at center-of-mass (CoM) energies sqrt(s) = 13 TeV and sqrt(s) = 100TeV and dijet final states at sqrt(s) = 14 TeV. A functional relation of the form y(n) = a · nb + c was found between theenergy consumed and the number of events, n, compatible with linearity within 3 standard deviations at 100 TeV and up to 4.7 standard deviations at 13 TeV. Additionally, it was found that up to 108 simulated events, the power consumption of the CPU running HERWIG remained constant to a good approximation, suggesting that the energy consumption of the CPU, and therefore the emissions, up to a multiplication factor, can be fully parametrised by the duration of the event generation, a finding supported by previous works [2, 3]. Considering the total events recorded by the Large Hadron Collider (LHC) during 2024 [4], the emissions for generating 10^16 events were estimated at (6.75 ± 1.72) · 10^4 tonnes of CO2e for sqrt(s) = 13 TeV and (2.86 ± 2.17) · 106^2 tonnes of CO2e for sqrt(s) = 100 TeV. The large uncertainties, particularly for sqrt(s) = 100 TeV, arise because the extrapolation extends far beyond the collected data range. Furthermore, allowing the exponent b to vary as a free parameter in the model makes the fit especially sensitive to uncertainties, as small changes in b are exponentially amplified at high values of n. Nevertheless, these results are of great value since they provide an order-of-magnitude estimate of the environmental impact of Monte Carlo event generators at LHC scales.