Speaker
Description
The use of heterogeneous CPU–GPU architectures is becoming an increasingly important consideration for LHC experiments in view of the growing computing demands of the HL-LHC era. WLCG sites and LHC experiments must make decisions in the short to medium term on the deployment and integration of GPUs, in order for these resources to be available and effectively exploited for HL-LHC operations. A key factor in this decision process is the cost-effectiveness of GPUs when running HEP software.
The AdePT project has demonstrated that full Monte-Carlo simulations can be efficiently adapted to GPUs and has been integrated into the ATLAS, CMS and LHCb experiments software frameworks. This integration provides simulation capabilities that are close to production use, with excellent physics agreement with established CPU-based workflows. The energy efficiency of GPU-accelerated simulation has been evaluated in realistic, production-like environments using modern hardware, enabling quantitative comparisons of cost and energy consumption relative to traditional CPU-based simulation. In addition, mitigation strategies such as power and frequency capping have been investigated to further optimize physics throughput per Watt.