NVIDIA GTC 2018
Canonical
on 14 March 2018
Tags: cloud , GPU , IoT , kubernetes , nvidia , TensorFlow
This article is more than 5 years old.
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 everything from healthcare to virtual reality, accelerated analytics, self-driving cars, and much more.
This year the Ubuntu team will be on site at booth 1227. Join us for demos on
- Using Kubeflow to manage Tensorflow jobs from desktop to servers and cloud.
- Building a complete, on premise AI platform using automation tools (MAAS and Juju) to deploy and manage Kubernetes on bare metal.
- How worker nodes with and without GPU’s are automatically identified to execute Tensorflow jobs.
Talks:
Using Containers for GPU Workloads: March 28, 10:00AM – 10:50AM – Room 210E
Presenters: Christian Brauner – Software Engineer, Canonical Ltd. & Serge Hallyn: Principal Engineer, Cisco
Learn how to use containers for efficient GPU utilization to achieve bare-metal performance for computationally intensive workloads. We’ll show how NVIDIA tools and libraries can be used to achieve drop-in GPU support and efficient GPU feature integration for container runtimes, and illustrate how to leverage system containers to run complex statistical models on NVIDIA GPUs.
Tell us about your project
Come discuss with our team to find out how Ubuntu can help you in your AI and deep learning projects.
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