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First steps towards enabling graphics processing unit (GPU) acceleration of the task-parallel smoothed particle hydrodynamics (SPH) solver SWIFT. Novel combinations of algorithms enable SWIFT to be a truly heterogeneous software leveraging task-parallelism on CPUs for memory-bound computations concurrently with GPUs for compute-bound computations. Effects of CPU–GPU communication latency minimized. GPU accelerated task-based parallelism is up to 3.5 speedup. GPU-acceleration is also demonstrated to give a 29 per cent improvement in energy efficiency in comparison to CPU-only baselines.
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This page is a summary of: Task-Parallelism in SWIFT for Heterogeneous Compute Architectures, RAS Techniques and Instruments, January 2026, Oxford University Press (OUP),
DOI: 10.1093/rasti/rzag008.
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