Comparing neural network training performance between Elixir and Python

  • The Conclusion from the paper:

        6 Conclusion
        In this article, we concluded that Elixir took more time in both datasets ana-      lyzed compared 
        to Python while demanding more Graphic RAM on peaks. We observed    that RAM usage is 
        an exception to the other metrics as Elixir con- sumed on average  42% and 33% less RAM 
        than Python, showing that Elixir has better memory management  for these test cases.
        As for usability, we observed that Python has much more documentation, material, 
        and available libraries for dataset preparation, model creation, and training.  This 
        was expected as Python is already much more consolidated in the machine learning 
        market. However, the Nx library was a significant improve- ment to Elixir, allowing 
        the language to be used for neural network creations much more efficiently than before Nx.

  • from the paper: "This work aims to compare the results of Python and Elixir on training convolutional neural networks (CNN) using MNIST and CIFAR10 datasets, concluding that Python achieved overall better results, and that Elixir is already a viable alternative."

  • I also want to note they are using older versions of Axion and Nx