NVIDIA GTC 2018
Canonical
on 14 March 2018
Tags: cloud , GPU , IoT , kubernetes , nvidia , TensorFlow
This article is more than 8 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.
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