Radium looks to speed up AI and ML jobs in cloud datacenters

Today, Radium, a startup that aims to use artificial intelligence and machine learning to extract more computing power from cloud hardware, announced it was leaving stealth mode and deploying its solutions to cloud datacenters run by Cyxtera in Toronto, the New York and New Jersey metro area, and Silicon Valley. The main product, called Launchpad, lets users start and shut down projects on bare metal machines, eliminating the extra layers of hypervisors and virtualization software. Radium offered benchmark tests on machine learning jobs that showed speed increases ranging from 30% and 140%. "Our initial testing shows that bare metal servers offer a good cloud computing platform for the high-performance deep learning and inference workloads required for these types of applications," said Srinivasa Narasimhan, a professor at Carnegie Mellon's School of Computer Science, who has been working with the company to test its product. Many cloud products rely heavily on virtualization software layers, or "hypervisors," that allow one physical machine to simulate a variety of smaller machines that appear independent to users.