How to use GPUs in OpenShift 3.6 (Still Alpha)

How to use GPUs in OpenShift 3.6 (Still Alpha)

Run general-purpose compute workloads on Graphics Processing Units (GPUs) with these instructions for using OpenShift 3.6 GPU support in Kubernetes. GPU support in Kubernetes remains in alpha through the next several releases. The Resource Management Working Group is driving progress towards stabilizing these interfaces.

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Jupyter on OpenShift Part 2: Using Jupyter Project Images

Jupyter on OpenShift Part 2: Using Jupyter Project Images

The quickest way to run a Jupyter Notebook instance in a containerised environment such as OpenShift, is to use the Docker-formatted images provided by the Jupyter Project developers. Unfortunately the Jupyter Project images do not run out of the box with the typical default configuration of an OpenShift cluster.

In this second post of this series about running Jupyter Notebooks on OpenShift, I am going to detail the steps required in order to run the Jupyter Notebook software on OpenShift.

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Jupyter on OpenShift: Using OpenShift for Data Analytics

Jupyter on OpenShift: Using OpenShift for Data Analytics

It is a commonly used catch phrase to say how ‘Software is Eating The World’ and how all companies are now software companies. It isn’t just the software that is important though, it is the data which is being generated by these systems. At the extreme end of the spectrum, companies can generate or collect quite massive data sets, and this is often referred to as the realm of ‘Big Data’.

No matter how much data you have, it is of no value if you don’t have a way to analyse the data and visualise the results in a meaningful way that you can act upon.

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How to use GPUs in OpenShift and Kubernetes

How to use GPUs in OpenShift and Kubernetes

Running general-purpose compute workloads on Graphics Processing Units (GPUs) has become increasingly popular recently in a wide range of application domains, mirroring the increased ubiquity of deploying applications in Linux containers. Thanks to community participant Clarifai, Kubernetes became able to schedule workloads depending on GPUs beginning with version 1.3, enabling us to develop applications that are on the cutting edge of both trends with Kubernetes or OpenShift.

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Intro to Machine Learning using Tensorflow – Part 1

Intro to Machine Learning using Tensorflow - Part 1

Tensorflow is an open-source software library created by Google for Machine Intelligence. And Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text with others. Throughout this series, we’ll be using these two applications primarily, but we’ll also venture into other popular frameworks as well. By the end of this post, you’ll be able to run a linear regression (the “hello world” of ML) inside a container you built running in a cloud.

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OpenShift Commons Big Data SIG #2: Running Apache Spark Natively on Kubernetes with OpenShift

Red Hat OpenShift Commons

In this second meeting of the Big Data Special Interest Group, our guest speaker was Erik Erlandson, Senior Software Engineer at Red Hat on the Big Data team. Erik gave a brief introduction to RDD (Resilient Distributed Dataset) in the context of Apache Spark and then dove right into a demo of running Apache Spark natively on OpenShift, Red Hat’s Enterprise-ready Kubernetes for developers.

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