Work

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

Year: 2024

Type: article

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.

Source: Concurrency and Computation Practice and Experience

DOI: 10.1002/cpe.8313

Author: Giuseppe Bilotta

Institutions: Istituto Nazionale di Geofisica e Vulcanologia, INGV Osservatorio Etneo

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,900

OpenAlex ID: W4403882273

FWCI: 0.641

Cites: 44

Cited by: 2

Related to: 10