March 26, 2020 3 min

Element AI Showcases Element AI Orkestrator GPU Management Product at NVIDIA GTC Digital

Canadian AI solutions developer presents newest technology that helps enterprises adopting AI to efficiently manage GPU clusters and optimize their compute and storage resources

SANTA CLARA, Calif.—APRIL 3, 2020—NVIDIA GTC DigitalElement AI, a global developer of artificial intelligence-powered (AI) services and software, today is showcasing its solutions lineup for NVIDIA GTC Digital 2020 online. Element AI CEO and Co-founder, JF Gagné presents “Enabling Human-Machine Collaboration”, demonstrating how Element AI Orkestrator effectively schedules and allocates GPU clusters for optimal workload balancing on the NVIDIA GTC Inception Startup Showcase.

Element AI Orkestrator was designed for AI practitioners, and the IT staff that supports them, as a workload scheduling tool, built in response to the company’s need to optimize its own computing resources. A software-as-a-service (SaaS) version of Element AI Orkestrator is available now, with an on-premises version expected in Spring 2020.

Element AI Orkestrator is the first product in a suite of tools from Element AI that will help organizations become AI-ready by accelerating the end-to-end process of building and deploying AI models and applications. NVIDIA and Element AI play crucial roles in helping end-users address growing computing power and storage requirements to accommodate heavier GPU-based workloads. Element AI Orkestrator helps manage the increasingly complex resource distribution and management that AI computing requires.

“Element AI Orkestrator has a lot of potential for customers who have made significant investments in their AI infrastructures,” said John Barco, senior director of NVIDIA DGX software at NVIDIA. “Element AI Orkestrator can help end-users make the most efficient use and scale of their computing resources,” added Barco.

Customers can future proof their IT infrastructures through optimized utilization of GPU clusters with Element AI Orkestrator. AI practitioners can build quality models and remove most of the engineering heavy lifting required to efficiently schedule and allocate GPU cluster usage.

“We originally created Element AI Orkestrator for our own internal data science teams and developers conducting AI research. The tool became so useful, our customers began requesting it,” said Ludwig Gamache, Head of IT at Element AI. “Our own GPU usage is over 90 per cent on average; by using the Element AI Orkestrator tool we were able to grow our cluster by 36 times, yet required minimal additions to our IT staff,” added Gamache.

Watch a video illustration (1min. 20sec.) of Element AI Orkestrator here: https://vimeo.com/390065094.

To learn more about Element AI and its AI-powered products, visit: https://www.elementai.com/

To request a sales call or product demonstration for Element AI Orkestrator contact: elementai.com/contact

About Element AI

Element AI is a global developer of AI software and solutions that help people and machines work smarter, together. Founded in 2016 by serial entrepreneurs including JF Gagné and A.M.Turing Award recipient, Yoshua Bengio, PhD, Element AI turns cutting-edge research and industry expertise into software solutions that exponentially learn and improve. Its end-to-end offering, including advisory services, AI enablement tools and products, aims at helping large organizations operationalize AI and create real business impact. Element AI maintains a strong connection to academia through research collaborations and takes a leadership position in policymaking around the impact of technology on society. https://www.elementai.com.

Press Contacts for Element AI:

Kevin G Clark, Senior PR Manager
Kevin.clark@elementai.com
Cell: +1 (514) 754-0343

© Element AI Inc., 2020, all rights reserved. Element AI™ and the Element AI logo are protected by trademarks of Element AI Inc. Element AI Orkestrator is a trademark of Element AI, and may be registered or pending registration in several jurisdictions. Other trademarks used in this document may be trademarks of the manufacturers or vendors of their respective products.