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CodeReady Containers with GPU for Data Science

Lots of Data Scientists want to focus on model building. Just using a local Jupyter Notebook can be a limitation if you want to: create scalable Machine Learning systems test local private data ingestion contribute to Kubeflow tune your model serving pipeline You can build an All-in-One Kubernetes environment with NVIDIA GPU for Data Science on your local PC or one bare-metal cloud server, let’s see how CodeReady Containers works.

Open Data Hub v0.5.1 release

Open Data Hub v0.5.1 was released February 16, 2020. Release node: https://opendatahub.io/news/2020-02-16/odh-release-0.5.1-blog.html Open Data Hub includes many tools that are essential to a comprehensive AI/ML end-to-end platform.

NVIDIA GPU Operator with OpenShift 4.3 on Red Hat OpenStack Platform 13

The NVIDIA GPU Operator has been available as a Beta since 2020, Jan 27, it’s a technical preview release: https://github.com/NVIDIA/gpu-operator/release The GPU Operator manages NVIDIA GPU resources in an OpenShift cluster and automates tasks related to bootstrapping GPU nodes.

OPAE with Intel FPGA PAC with Arria 10 GX

OPAE is the Open Programmable Acceleration Engine, a software framework for managing and accessing programmable accelerators (FPGAs): https://01.org/opae The OPAE SDK is open source and available in this git: https://github.

How to enable NVIDIA T4 GPU with podman

We will enable GPU with Podman on a RHEL 8.1 system with a NVIDIA Tesla T4: Take a RHEL 8.1 system: [egallen@lab0 ~]$ cat /etc/redhat-release Red Hat Enterprise Linux release 8.

Red Hat OpenStack Platform 15 standalone

If you need to deploy quickly a testing Red Hat Openstack Platform environment, you can use standalone deployment available since Red Hat OpenStack Platform 14.

OpenShift 4.2 on Red Hat OpenStack Platform 13 + GPU

Red Hat OpenShift Container Platform 4.2 introduces the general availability of full-stack automated deployments on OpenStack. With OpenShift 4.2, containers can be managed across multiple public and private clouds, including OpenStack.

NVIDIA vGPU software and license server with RHOSP 15

We will describe the steps to try and download NVIDIA GRID software: Create a NVIDIA account Redeem your Product Activation Key (PAK) Download packages Prepare the VM and operating system of the license server based on RHEL 7.

NVIDIA vGPU with Red Hat OpenStack Platform 14

Red Hat OpenStack Platform 14 is now generally available \o/ NVIDIA GRID capabilities are available as a technology preview to support NVIDIA Virtual GPU (vGPU). Multiple OpenStack instances virtual machines can have simultaneous, direct access to a single physical GPU.

NVIDIA Tesla GPU PCI passthrough with Red Hat OpenStack Platform 13

Red Hat OpenStack Platform provides two ways to use NVIDIA Tesla GPU accelerators with virtual instances: GPU PCI passthrough (only one physical GPU per instance) vGPU GRID (one physical GPU can be shared to multiple instances, Tech Preview OSP14) This blog post is intended to show how to setup GPU PCI passthrough.

USB Passthrough with Red Hat OpenStack Platform 13

Some OpenStack users users would like to attach USB devices to OpenStack instances for security or legacy applications. For example, a security application which run inside an OpenStack instance could require access to a Java card from an USB Gemalto eToken: