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Article

Comparison of the Usability of Apple M1 Processors for Various Machine Learning Tasks

by
David Kasperek
*,
Michal Podpora
and
Aleksandra Kawala-Sterniuk
Department of Computer Science, Opole University of Technology, Proszkowska 76, 45-758 Opole, Poland
*
Author to whom correspondence should be addressed.
Sensors 2022, 22(20), 8005; https://doi.org/10.3390/s22208005
Submission received: 9 September 2022 / Revised: 7 October 2022 / Accepted: 17 October 2022 / Published: 20 October 2022
(This article belongs to the Special Issue Intelligent Sensors and Machine Learning)

Abstract

In this paper, the authors have compared all of the currently available Apple MacBook Pro laptops, in terms of their usability for basic machine learning research applications (text-based, vision-based, tabular). The paper presents four tests/benchmarks, comparing four Apple Macbook Pro laptop versions: Intel based (i5) and three Apple based (M1, M1 Pro and M1 Max). A script in the Swift programming language was prepared, whose goal was to conduct the training and evaluation process for four machine learning (ML) models. It used the Create ML framework—Apple’s solution dedicated to ML model creation on macOS devices. The training and evaluation processes were performed three times. While running, the script performed measurements of their performance, including the time results. The results were compared with each other in tables, which allowed to compare and discuss the performance of individual devices and the benefits of the specificity of their hardware architectures.
Keywords: processor architectures; neural processing unit; neural processing cores; NPU benchmark; Apple M1; CoreML; Neural Engine; machine learning; deep learning processor architectures; neural processing unit; neural processing cores; NPU benchmark; Apple M1; CoreML; Neural Engine; machine learning; deep learning

Share and Cite

MDPI and ACS Style

Kasperek, D.; Podpora, M.; Kawala-Sterniuk, A. Comparison of the Usability of Apple M1 Processors for Various Machine Learning Tasks. Sensors 2022, 22, 8005. https://doi.org/10.3390/s22208005

AMA Style

Kasperek D, Podpora M, Kawala-Sterniuk A. Comparison of the Usability of Apple M1 Processors for Various Machine Learning Tasks. Sensors. 2022; 22(20):8005. https://doi.org/10.3390/s22208005

Chicago/Turabian Style

Kasperek, David, Michal Podpora, and Aleksandra Kawala-Sterniuk. 2022. "Comparison of the Usability of Apple M1 Processors for Various Machine Learning Tasks" Sensors 22, no. 20: 8005. https://doi.org/10.3390/s22208005

APA Style

Kasperek, D., Podpora, M., & Kawala-Sterniuk, A. (2022). Comparison of the Usability of Apple M1 Processors for Various Machine Learning Tasks. Sensors, 22(20), 8005. https://doi.org/10.3390/s22208005

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