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

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

JOURNAL=Frontiers in Big Data

VOLUME=Volume 7 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2024.1485344

DOI=10.3389/fdata.2024.1485344

ISSN=2624-909X

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.