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

Thispaper 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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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2023-06, Vol.23 (12), p.5424
Main Authors: Kasperek, David, Antonowicz, Pawel, Baranowski, Marek, Sokolowska, Marta, Podpora, Michal
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Business performance management
Cognitive tasks
Comparative analysis
Computational linguistics
Computer industry
Datasets
Deep learning
International economic relations
Language processing
Machine learning
Natural language interfaces
Neural networks
neural processing cores
neural processing unit
NPU benchmark
Optimization
Performance evaluation
Playgrounds
processor architectures
Programming languages
Research methodology
Software
Usability
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Summary:Thispaper 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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s23125424