This blog is part of our DRA series, continuing from our earlier posts: Introduction to DRA, Enabling DRA with Kind, and MIG with DRA . This post focuses on pre-DRA vs post-DRA GPU management on Rafay upstream Kubernetes clusters.
This is a multi-series blog on GPUs, how they intersect with Kubernetes and containers. In this blog, we will discuss how CPUs and GPUs are architecturally similar and different. We will also review when it is ideal to use a CPU vs a GPU.
This is part of a blog series on AI/Machine Learning. In the previous blog, we discussed Jupyter Notebooks, how they are different and the challenges organizations run into at scale with it. In this blog, we will look at organizations can use JupyterHub to take to provide access to Jupyter notebooks as a centralized service for their data scientists.
Jupyter Notebook is open-source software created and maintained by the Jupyter community. A Jupyter notebook allows for the creation and sharing of documents with code and rich text elements. It works with over 40 programming languages including Python, R, and Ruby making it versatile and flexible for data scientists. In this introductory blog to Jupyter notebooks, we will look at "why it exists" and "what it looks like".
