Simulations based on particle methods, such as Smoothed Particle Hydrodynamics (SPH), are known to be computationally demanding. While such methods have for long been executed in parallel on multi-core CPUs, in recent years the increasing adoption of many-core accelerators, such as GPUs. However, hardware fragmentation and vendor-specific programming interfaces are still characterizing their market. Hence, support for various hardware configurations may easily lead to non-trivial and less maintainable implementations. To leverage over some higher-level specifications have become available recently, such as the SYCL programming standard, this work highlights the initial effort in adopting the SYCL standard for the execution of SPHinXsys, an open-source multi-physics library. The result is an execution model able to run the same implementation on variable (heterogeneous) hardware, with considerable speed-up compared to the current multi-core CPU parallelization. Among others, representation of data-structures for parallel access, communication strategies, and parallel methods for data sorting will be topics discussed in depth. Benchmarks has also been presented, showcasing performance comparisons between the current multi-core CPU implementation and the newly introduced SYCL parallelization with a GPU back-end.
@article{arxiv.2603.11868,
title = {Towards heterogeneous parallelism for SPHinXsys},
author = {Xiangyu Hu and Alberto Guarnieri},
journal= {arXiv preprint arXiv:2603.11868},
year = {2026}
}