Abstract
The recent progress in parallel hardware architectures with deeper vector pipelines or many-cores technologies brings opportunities for HEP experiments to take advantage of SIMD and SIMT computing models. Launched in 2013, the GeantV project studies performance gains in propagating multiple particles in parallel, improving instruction throughput and data locality in HEP event simulation on modern parallel hardware architecture. Due to the complexity of geometry description and physics algorithms of a typical HEP application, performance analysis is indispensable in identifying factors limiting parallel execution. In this report, we will present design considerations and preliminary computing performance of GeantV physics models on coprocessors (Intel Xeon Phi and NVidia GPUs) as well as on mainstream CPUs.
Highlights
Recent discoveries in experimental High Energy Physics (HEP) would not be possible without leveraging advances in scientific computing, especially in the areas of simulation, reconstruction, and physics analysis for large-scale data sets
For more than two decades, HEP programs have taken advantage of automatic performance gains coming from increases in processor clock speed and high throughput computing using either local clusters (Farms) or distributed resources around the world (GRIDs)
Demands for computing power are ever-increasing for future HEP programs, especially for High-luminosity LHC experiments
Summary
G Amadio, A Ananya, J Apostolakis, A Aurora, M Bandieramonte, A Bhattacharyya C Bianchini , R Brun, P Canal, F Carminati, G Cosmo, L Duhem, D Elvira, G Folger, A Gheata, M Gheata , I Goulas, R Iope, S Y Jun, G Lima, A Mohanty, T Nikitina, M Novak, W Pokorski, A Ribon, R Seghal O Shadura, S Vallecorsa, S Wenzel, and Y Zhang
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