From <scp>GPU</scp> to <scp>CPU</scp> (and Beyond): Extending Hardware Support in <scp>GPUSPH</scp> Through a <scp>SYCL</scp>‐Inspired Interface

ABSTRACT While most software is originally designed for serial or parallel execution on CPU, and porting to GPU comes later in its development, GPUSPH was designed from the ground up to run on GPUs using CUDA. Making it accessible to a wider audience by introducing support for other computational hardware, and in particular CPUs, poses challenges that are complementary to the ones normally faced when porting CPU code to GPU. We present the approach we have adopted to support CPUs as computational devices in GPUSPH with minimal code changes and low developer effort. Detailed benchmarks illustrating the performance of the implementation and its scalability across multiple cores in both single‐socket and NUMA configurations show good strong and weak scaling.

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Publication Details

Journal
Concurrency and Computation Practice and Experience
Published
2024-10-28
DOI
https://doi.org/10.1002/cpe.8313
Citations
2
Primary Topic
Fluid Dynamics Simulations and Interactions
Type
article
Field-Weighted Citation Impact
0.75
Controls
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article

From GPU to CPU (and Beyond): Extending Hardware Support in GPUSPH Through a SYCL‐Inspired Interface

Giuseppe Bilotta
2 citations
Concurrency and Computation Practice and Experience
Fluid Dynamics Simulations and Interactions
0.75
article

From GPU to CPU (and Beyond): Extending Hardware Support in GPUSPH Through a SYCL‐Inspired Interface

Giuseppe Bilotta
article en
2 citations

Abstract

ABSTRACT While most software is originally designed for serial or parallel execution on CPU, and porting to GPU comes later in its development, GPUSPH was designed from the ground up to run on GPUs using CUDA. Making it accessible to a wider audience by introducing support for other computational hardware, and in particular CPUs, poses challenges that are complementary to the ones normally faced when porting CPU code to GPU. We present the approach we have adopted to support CPUs as computational devices in GPUSPH with minimal code changes and low developer effort. Detailed benchmarks illustrating the performance of the implementation and its scalability across multiple cores in both single‐socket and NUMA configurations show good strong and weak scaling.

Concurrency and Computation Practice and ExperienceVol. 37(1)
Istituto Nazionale di Geofisica e Vulcanologia (IT)
Openalex Percentile: Top 32%
Fluid Dynamics Simulations and Interactions
0.75
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