Speakers
Description
Physicists at the Large Hadron Collider (LHC), near Geneva,
Switzerland, are preparing their experiments for the high
luminosity (HL) era of proton-proton collision data-taking. In
addition to detector hardware research and development for
upgrades necessary to cope with the more than two-fold increase
in instantaneous luminosity, physicists are investigating
potential heterogeneous computing solutions to address CPU
limitations that could be detrimental to an otherwise successful
physics program.
At the dawn of supercomputers employing a wide range of
architectures and specifications, it is crucial that experiments'
software be much as possible abstracted away from the underlying
hardware implementation in order to utilize the vast array of
these machines. New developments in application programming
interfaces (APIs) aim to be architecture-independent, providing
the ability to write single-source codes that can be compiled for
virtually any hardware. In this talk, we present the details of
our work on a cross-platform software prototyping with Kokkos, a
single source, performant parallel C++ API that provides hardware
backends for wide range of parallel architectures, including
NVIDIA, AMD, Intel, OpenMP and pThreads, and SYCL, an abstraction
layer whose specification is defined by the Khronos Group and
members from industry-leading entities such as Intel. Using
ATLAS’s new fast calorimeter simulations codes, FastCaloSim, as a
testbed, we evaluate Kokkos and SYCL in terms of its
heterogeneity and its performance with respect to other parallel
computing APIs.
