Dell releases Omnia to manage AI and analytics workloads
Dell has released Omnia, an open-source software package aimed at simplifying AI and compute-intensive workload deployment and management.
Developed at Dell’s High Performance Compute (HPC) and AI Innovation Lab in collaboration with Intel and Arizona State University (ASU), Omnia automates the provisioning and management of HPC, AI, and data analytics to create a pool of hardware resources.
"As AI with HPC and data analytics converge, storage and networking configurations have remained in siloes, making it challenging for IT teams to provide required resources for shifting demands," said Peter Manca, senior vice president of Integrated Solutions at Dell Technologies. "With Dell's Omnia open source software, teams can dramatically simplify the management of advanced computing workloads, helping them speed research and innovation."
How does Omnia work?
Available now, Omnia is essentially a set of Ansible playbooks of automation tasks that can be performed by software without human intervention. The playbooks can be used to speed up the deployment of converged workloads managed by Kubernetes and Slurm, as well as library frameworks, services and applications, Dell said.
Omnia works by automatically imprinting a software solution onto each server that has been assigned to the workload in question. Dell said that helps reduce time to deployment from days to just minutes for a wide range of converged workloads, such as HPC simulations, neural networks for AI or in-memory graphics processing for data analytics.
"Engineers from ASU and Dell Technologies worked together on Omnia's creation," said Douglas Jennewein, senior director of research computing, Arizona State University. "It's been a rewarding effort working on code that will simplify the deployment and management of these complex mixed workloads, at ASU and for the entire advanced computing industry."
In a related announcement, Dell said that it’s expanding its HPC on demand offering to now support VMware environments to include VMware Cloud Foundation, VMware Cloud Director, and VMware vRealize Operations. Beyond this, the company now offers Nvidia A30 and A10 Tensor Core GPUs as options for its Dell EMC PowerEdge R750, R750xa, and R7525 servers
Nvidia’s platform for AI startups passes 8,500 members
NVIDIA Inception, an acceleration platform for AI startups, has now surpassed 8,500 members. That’s about two-thirds of the total number of AI startups worldwide, as estimated by Pitchbook.
NVIDIA Inception is a programme built to accommodate every startup that is accelerating computing, at every stage in their journey. All programme benefits are free of charge and startups never have to give up equity to join.
Since Inception’s launch in 2016, it has grown more than tenfold. With total cumulative funding of over $60 billion and members in 90 countries, NVIDIA Inception is one of the largest AI startup ecosystems in the world. Growth has accelerated year over year, with membership increasing to 26% in 2020, and reaching 17% in the first half of 2021.
Data from across the world
Inception figures show the United States leads the world in terms of both the number of AI startups, representing nearly 27%, and the amount of secured funding, accounting for over $27 billion in cumulative funding. 42% of US-based startups were in California, with 29% in the San Francisco Bay Area.
Behind the US is China, in terms of both funding and company stage, with 12% of NVIDIA Inception members based there. India comes in third at 7%, with the UK right behind at 6%.
AI startups based in the US, China, India, and the UK account for just over half of all startups in NVIDIA Inception. Following in order after these are Germany, Russia, France, Sweden, Netherlands, Korea and Japan.
In terms of industries, healthcare, IT services, intelligent video analytics (IVA), media and entertainment (M&E) and robotics are the top five in NVIDIA Inception. AI startups in healthcare account for 16% of Inception members, followed by those in IT services at 15%.
More than 3,000 AI startups have joined Nvidia Inception since 2020. “Some countries are accelerating their ecosystem of AI startups by investing money and encouraging the local players to create more companies,” said Serge Lemonde, global head of Nvidia Inception, in an interview with VentureBeat.
“In our programme, what we are looking at is to help them all,” Lemonde said. “The lesson here is really having this window on the landscape and helping the startups all around the world — [this] is helping us understand the new trends. We can help more startups by developing our software and platforms for the upcoming trends.”