Evaluating Performance and Energy Efficiency of Parallel Programming Models in Heterogeneous Computing Systems

We provide a detailed evaluation of several parallel programming models, emphasizing both performance and energy efficiency in heterogeneous computing systems. The evaluation employs a diverse array of hardware, including Intel Xeon and AMD Epyc CPUs, along with NVIDIA GPUs featuring Pascal, Turing, and Ampere architectures, and an AMD GPU with Vega10 architecture. We utilize SYCL, OpenMP, CUDA, and HIP for implementing benchmarks in 11 varied application domains, offering a comprehensive perspective on the capabilities of these programming models in diverse computing environments.

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Publication Details

Published
2024-09-15
DOI
https://doi.org/10.1109/iiswc63097.2024.00035
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluating Performance and Energy Efficiency of Parallel Programming Models in Heterogeneous Computing Systems

Bilal Erman Bilgin, İsmail Aktürk, Demirhan Sevim
Cloud Computing and Resource Management
article

Evaluating Performance and Energy Efficiency of Parallel Programming Models in Heterogeneous Computing Systems

Bilal Erman Bilgin, İsmail Aktürk, Demirhan Sevim
article en

Abstract

We provide a detailed evaluation of several parallel programming models, emphasizing both performance and energy efficiency in heterogeneous computing systems. The evaluation employs a diverse array of hardware, including Intel Xeon and AMD Epyc CPUs, along with NVIDIA GPUs featuring Pascal, Turing, and Ampere architectures, and an AMD GPU with Vega10 architecture. We utilize SYCL, OpenMP, CUDA, and HIP for implementing benchmarks in 11 varied application domains, offering a comprehensive perspective on the capabilities of these programming models in diverse computing environments.

Özyeğin University (TR)
Affordable and clean energy
Openalex Percentile: Top 60%
Cloud Computing and Resource Management
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