Hammad Ather, Sophie Berkman, Giuseppe Cerati, Matti Kortelainen, Ka Hei Martin Kwok, Steven Lantz, Seyong Lee, Boyana Norris, Michael Reid, Allison Reinsvold Hall, Daniel Riley, Alexei Strelchenko, Cong Wang
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引用次数: 0
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.
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