Exploring code portability solutions for HEP with a particle tracking test code

Hammad Ather; Sophie Berkman; Giuseppe Cerati; Matti J Kortelainen; Ka Hei Martin Kwok; Steven Lantz; Seyong Lee; Boyana Norris; Michael Reid; Allison Reinsvold Hall; Daniel Riley; Alexei Strelchenko; Cong Wang

doi:10.3389/fdata.2024.1485344

Exploring code portability solutions for HEP with a particle tracking test code

Front Big Data. 2024 Oct 23:7:1485344. doi: 10.3389/fdata.2024.1485344. eCollection 2024.

Authors

Affiliations

¹ Department of Computer and Information Science, University of Oregon, Eugene, OR, United States.
² Department of Physics and Astronomy, Michigan State University, East Lansing, MI, United States.
³ Computational Science and AI Directorate, Fermi National Accelerator Laboratory, Batavia, IL, United States.
⁴ Department of Physics, Cornell University, Ithaca, NY, United States.
⁵ Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States.
⁶ Physics Department, United States Naval Academy, Annapolis, MD, United States.
⁷ School of Computing, Clemson University, Clemson, SC, United States.

Abstract

Traditionally, high energy physics (HEP) experiments have relied on x86 CPUs for the majority of their significant computing needs. As the field looks ahead to the next generation of experiments such as DUNE and the High-Luminosity LHC, the computing demands are expected to increase dramatically. To cope with this increase, it will be necessary to take advantage of all available computing resources, including GPUs from different vendors. A broad landscape of code portability tools-including compiler pragma-based approaches, abstraction libraries, and other tools-allow the same source code to run efficiently on multiple architectures. In this paper, we use a test code taken from a HEP tracking algorithm to compare the performance and experience of implementing different portability solutions. While in several cases portable implementations perform close to the reference code version, we find that the performance varies significantly depending on the details of the implementation. Achieving optimal performance is not easy, even for relatively simple applications such as the test codes considered in this work. Several factors can affect the performance, such as the choice of the memory layout, the memory pinning strategy, and the compiler used. The compilers and tools are being actively developed, so future developments may be critical for their deployment in HEP experiments.

Keywords: code portability; heterogeneous architectures; heterogeneous computing; particle tracking; portability solutions.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. We thank the Joint Laboratory for System Evaluation (JLSE) for providing the resources for the performance measurements used in this work. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This material is based upon work by the RAPIDS Institute and the “HEP Event Reconstruction with Cutting Edge Computing Architectures” project, supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research and Office of High-Energy Physics, Scientific Discovery through Advanced Computing (SciDAC) program. This work was supported by the National Science Foundation under Cooperative Agreements OAC-1836650 and PHY-2323298; by the U.S. Department of Energy, Office of Science, Office of High Energy Physics under Award Number 89243023SSC000116; and by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, High Energy Physics Center for Computational Excellence (HEP-CCE) at Fermi National Accelerator Laboratory under B&R KA2401045. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy and by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics. The publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a non-exclusive, paid up, irrevocable, world-wide license to publish or reproduce the published form of the manuscript, or allow others to do so, for U.S. Government purposes. The DOE will provide public access to these results in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).