Power efficiency of HEP applications on CPU & GPU

<!--HTML-->The LHC generates an immense volume of data by colliding protons or heavy ions at extremely high energies, resulting in a multitude of particle interactions. These interactions are crucial for experiments conducted at the LHC, such as ATLAS, CMS, ALICE, and LHCb, and require recording, processing, and analysis. To address this data challenge, the WLCG collaborates globally, offering computing resources and services to support these experiments. To understand which architecture is most suitable for certain kinds of jobs/workloads, we need to benchmark the workloads for the various experiments at CERN. My assignment involved benchmarking these workloads, especially MadGraph, on both CPU and GPU. The goal was to study the relationship between energy consumption and performance on different architectures.