Comparing neural network training performance between Elixir and Python

• URL: http://arxiv.org/abs/2210.13945v1
• Date: Tue, 25 Oct 2022 11:57:14 GMT
• Title: Comparing neural network training performance between Elixir and Python
• Authors: Lucas C. Tavano, Lucas K. Amin, Adolfo Gustavo Serra-Seca-Neto
• Abstract summary: Python has made a name for itself as one of the main programming languages. In February 2021, Jos'e Valim and Sean Moriarity published the first version of the Numerical Elixir (Nx) library.
• Score: 0.9023847175654603
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: With a wide range of libraries focused on the machine learning market, such as TensorFlow, NumPy, Pandas, Keras, and others, Python has made a name for itself as one of the main programming languages. In February 2021, Jos\'e Valim and Sean Moriarity published the first version of the Numerical Elixir (Nx) library, a library for tensor operations written in Elixir. Nx aims to allow the language be a good choice for GPU-intensive operations. This work aims to compare the results of Python and Elixir on training convolutional neural networks (CNN) using MNIST and CIFAR-10 datasets, concluding that Python achieved overall better results, and that Elixir is already a viable alternative.

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