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Blog posts tagged
"TensorFlow"

Canonical
26 July 2018

AI, ML, & Ubuntu: Everything you need to know

Cloud and server Webinar

AI and ML adoption in the enterprise is exploding from Silicon Valley to Wall Street. Ubuntu is the premier platform for these ambitions — from developer workstations, to racks, to clouds and to the edge with smart connected IoT. One of the joys that come with new developer trends are a plethora of new technologies ...

Canonical
4 June 2018

Kubernetes and OpenStack solving AI complexities at scale

Cloud and server Article

Stu Miniman and John Boyer of theCUBE interviewed Stephan Fabel, Director of Ubuntu Product and Development at the OpenStack Summit in Vancouver. Read on for the full interview, and to hear more on Kubernetes, Kubeflow and MicroK8s. OpenStack has entered a new phase, maturing to a point where those in attendance are serious about open ...

Canonical
14 March 2018

NVIDIA GTC 2018

Cloud and server Article

Event Information Date: March 27 – 29 City/State: San Jose, CA Location: San Jose McEnery Convention Center Booth: #1227 GTC is the premier AI and deep learning conference, providing unparalleled training, industry insights, and direct access to NVIDIA and industry experts — all in one place. It features the latest breakthroughs in everyt ...

Samuel Cozannet
27 March 2017

Job concurrency in Kubernetes: LXD and CPU pinning to the rescue

Ubuntu Article

A few days ago, someone shared with me a project to run video transcoding jobs in Kubernetes. During her tests, made on a default Kubernetes installation on bare metal servers with 40 cores & 512GB RAM, she allocated 5 full CPU cores to each of the transcoding pods, then scaled up to 6 concurrent tasks ...

Samuel Cozannet
9 March 2017

GPUs and Kubernetes for deep learning — Part 3/3: Automating Tensorflow

Cloud and server Article

Here we are. After having spent 21min reading how to build a GPU Kubernetes cluster on AWS, 7min on adding EFS storage, you want to get to the real thing, which is actually DO something with it. So today we are going to define, design, deploy and operate a Deep Learning pipeline. So what is ...