IT & Data Science

NVIDIA GTC 2020 – AI Cluster Orchestration

November 5, 2021
Fara Hain

AI has a productivity challenge – can we beat that challenge?

The availability of compute power, particularly Nvidia GPUs, have helped to fuel enormous growth of AI in the enterprise. But getting AI to production quickly and efficiently is still challenging:

  • Because data science workflows – Build, train and inference – have different compute needs, researchers find that resources remain idle much of the time, slowing their progress.
  • AI infrastructure is hard to build and manage and teams often find that managing this complexity hampers their productivity – DS is often managing infrastructure, leading to frustration

Watch the NVIDIA GTC Session below to learn how smart AI cluster orchestration can be used to solve AI productivity challenges. Understand how quotas, policies and job priorities can be used to share resources efficiently. Learn about using dynamic, rather than fixed allocation of resources, and how that increases productivity.

Also included: a short case study from a London-based research university, who utilized AI software orchestration to optimize models in just 2 days, as opposed to 49.

Fara Hain
VP Marketing

Marketers get a bad rap today, with many people assuming we're paid to trick people into buying things they don't need. :) I believe in marketing of a different sort; the creative expression of a brand, the humanizing of a corporate entity, and the important task of helping consumers find products that will make their lives easier. My experience, 20+ years in mostly B2B marketing, has involved all of those and then some. I have worked mostly in the software industry, and primarily at startups - with a short stint in venture capital along the way that taught me about the financial side of company building. I occasionally blog on my new favorite marketing topic, account based marketing, at https://medium.com/@FaraJHain

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