Jupyter Notebooks

Jupyter Notebooks are open-source documents that can be used to create, prototype, and share computational documents. They can be used for various purposes, including data science, scientific computing, computational journalism, and machine learning.

One of the biggest challenges of using Jupyter Notebooks for machine learning is related to the use of GPUs (needed to speed up machine learning computations). Unfortunately, Jupyter Notebooks reserve and hold a GPU the entire time the notebook is open, even when idle and not running Python code. Furthermore, machine learning experiments often comprise other distinct phases, such as data preparation and visualization, that do not require a GPU. These shortcomings prevent others from using the GPU, drive up GPU costs, and force administrators to restrict GPU access.

Robbie solves this problem by enabling users to access high-performance GPUs in a Jupyter Notebook, whether hosted on a local machine, a non-GPU notebook server, or Google Colab.

There are three ways to access GPUs via Robbie in your Jupyter Notebook:

• Robbie Remote Function

• Robbie Magic

• Robbie Notebook Runner