The first generation of exascale systems will include a variety of machine
architectures, featuring GPUs from multiple vendors. As a result, many
developers are interested in adopting portable programming models to avoid
maintaining multiple versions of their code. It is necessary to document
experiences with such programming models to assist developers in understanding
the advantages and disadvantages of different approaches.
To this end, this paper evaluates the performance portability of a SYCL
implementation of a large-scale cosmology application (CRK-HACC) running on
GPUs from three different vendors: AMD, Intel, and NVIDIA. We detail the
process of migrating the original code from CUDA to SYCL and show that
specializing kernels for specific targets can greatly improve performance
portability without significantly impacting programmer productivity. The SYCL
version of CRK-HACC achieves a performance portability of 0.96 with a code
divergence of almost 0, demonstrating that SYCL is a viable programming model
for performance-portable applications.Comment: 12 pages, 13 figures, 2023 International Workshop on Performance,
Portability & Productivity in HP