As a Data Scientist, I want to work on an RStudio Server image managed by Kubernetes with GPU capability. The motivation for doing this is that I can then access a machine learning rig that is 1) scale invariant (same from desktop to Cloud), 2) leverages Kubernetes for scheduling and 3) taps me into the … Continue reading
Tag Archives: R
R with (external) GPU
We are going to mess around with some of the R gpu packages using our eGPU Rig. Look here for how to set up RStudio and then use the gpuR, gputools and keras/tensorflow packages against an eGPU. This blog post has been moved to www.emergile.com Continue reading
SparkR with OpenShift
Let’s set up a data science workbench on OpenShift (docker/kubernetes). The components will be an RStudio Server executing SparkR instructions to a remote Apache Spark instance, all hosted within a local OpenShift cluster instance. Examples include processing AWS S3 Bucket hosted data from Spark. So saddle up and ride ole’ Roxy all the way! This lab is another in … Continue reading
Jupyter and R with OpenShift
UPDATE – Visit SparkR with OpenShift for lastest r-notebook/OpenShift solution. – UPDATE The cool kids are using Jupyter notebooks. But we are going to step it up a notch by hosting an R-enabled Jupyter notebook on OpenShift. Max Bugger, may he rest-in-peace, will show you how. This lab is another in the OpenShift MiniLabs series. This blog post has been … Continue reading
R using RStudio Server with OpenShift
Details at http://www.emergile.com Continue reading
Drools Rules Rsynchronicity
This post continues experimenting with the sample application known as Weightwatcher to showcase a number of new technologies and techniques including: The all-in-one Vagrant image for OpenShift 3 The OpenShift Origin 3 oc rsync feature Drools 6.3.0.FINAL KIE Execution Server (Decision Server) A method for rule life cycle management with Containers Continue reading
RStudio Server as a Docker Container
[ UPDATE ] A new and improved approached to standing up a RStudio Server as a container instance can be found here. This post is an example of how to make it easy to distribute a functional RStudio Server environment for R as a single pre-baked image which can be installed in 2 steps. The … Continue reading