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Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks

This paper compares the usability of various Apple MacBook Pro laptops were tested for basic machine learning research applications, including text-based, vision-based, and tabular data. Four tests/benchmarks were conducted using four different MacBook Pro models—M1, M1 Pro, M2, and M2 Pro. A script...

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Detalles Bibliográficos
Autores principales: Kasperek, David, Antonowicz, Pawel, Baranowski, Marek, Sokolowska, Marta, Podpora, Michal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305298/
https://www.ncbi.nlm.nih.gov/pubmed/37420589
http://dx.doi.org/10.3390/s23125424
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author Kasperek, David
Antonowicz, Pawel
Baranowski, Marek
Sokolowska, Marta
Podpora, Michal
author_facet Kasperek, David
Antonowicz, Pawel
Baranowski, Marek
Sokolowska, Marta
Podpora, Michal
author_sort Kasperek, David
collection PubMed
description This paper compares the usability of various Apple MacBook Pro laptops were tested for basic machine learning research applications, including text-based, vision-based, and tabular data. Four tests/benchmarks were conducted using four different MacBook Pro models—M1, M1 Pro, M2, and M2 Pro. A script written in Swift was used to train and evaluate four machine learning models using the Create ML framework, and the process was repeated three times. The script also measured performance metrics, including time results. The results were presented in tables, allowing for a comparison of the performance of each device and the impact of their hardware architectures.
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spelling pubmed-103052982023-06-29 Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks Kasperek, David Antonowicz, Pawel Baranowski, Marek Sokolowska, Marta Podpora, Michal Sensors (Basel) Article This paper compares the usability of various Apple MacBook Pro laptops were tested for basic machine learning research applications, including text-based, vision-based, and tabular data. Four tests/benchmarks were conducted using four different MacBook Pro models—M1, M1 Pro, M2, and M2 Pro. A script written in Swift was used to train and evaluate four machine learning models using the Create ML framework, and the process was repeated three times. The script also measured performance metrics, including time results. The results were presented in tables, allowing for a comparison of the performance of each device and the impact of their hardware architectures. MDPI 2023-06-08 /pmc/articles/PMC10305298/ /pubmed/37420589 http://dx.doi.org/10.3390/s23125424 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kasperek, David
Antonowicz, Pawel
Baranowski, Marek
Sokolowska, Marta
Podpora, Michal
Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks
title Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks
title_full Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks
title_fullStr Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks
title_full_unstemmed Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks
title_short Comparison of the Usability of Apple M2 and M1 Processors for Various Machine Learning Tasks
title_sort comparison of the usability of apple m2 and m1 processors for various machine learning tasks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305298/
https://www.ncbi.nlm.nih.gov/pubmed/37420589
http://dx.doi.org/10.3390/s23125424
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