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Shadura, O.

Publications and source records attributed to Shadura, O..

Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access

Computing plays a significant role in all areas of high energy physics. The Snowmass 2021 CompF4 topical group's scope is facilities R&D, where we consider "facilities" as the computing hardware and software infrastructure inside the data centers plus the networking between data centers, irrespective of who owns them, and what policies are applied for using them. In other words, it includes commercial clouds, federally funded High Performance Computing (HPC) systems for all of science, and systems funded explicitly for a given experimental or theoretical program. This topical group report summarizes the findings and recommendations for the storage, processing, networking and associated software service infrastructures for future high energy physics research, based on the discussions organized through the Snowmass 2021 community study.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

GeantV: Results from the Prototype of Concurrent Vector Particle Transport Simulation in HEP

Full detector simulation was among the largest CPU consumers in all CERN experiment software stacks for the first two runs of the Large Hadron Collider. In the early 2010s, it was projected that simulation demands would scale linearly with increasing luminosity, with only partial compensation from increasing computing resources. The extension of fast simulation approaches to cover more use cases that represent a larger fraction of the simulation budget is only part of the solution, because of intrinsic precision limitations. The remainder corresponds to speeding up the simulation software by several factors, which is not achievable by just applying simple optimizations to the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport code in order to benefit from features of fine-grained parallelism, including vectorization and increased locality of both instruction and data. This paper provides an extensive presentation of the results and achievements of this R&D project, as well as the conclusions and lessons learned from the beta version prototype.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗