GPU maker sees 60% increase in channel unit as enterprises turn to cloud to manage WFH
GPU maker Nvidia is seeing a surge in companies joining its Cloud Service Provider partner program as enterprises turn to the cloud to address their large numbers of work-from-home employees.
The Lowdown: The company this week said during the first half of the year – as the COVID-19 pandemic spread around the world and forced businesses to temporarily shutter their offices and send employees home to work – membership in its cloud provider program grew by 60%. That includes 22 new partners from Europe and another 10 from North America.
The Details: Membership in the Cloud Service Provider (CSP) program now stands at more than 100 members, with Europe and North America accounting for more than 80% of those members.
Most organizations had employees work remotely to enable social distancing in hopes of mitigating the spread of the novel coronavirus as it made its way across the world in the late winter and early spring. To adapt to the suddenly mobile workforce and to continue to manage their IT environments, many companies turned to the cloud, speeding up a trend that already was well underway before the public health crisis hit.
The shift to teleworking will likely be permanent for growing numbers of workers. About 52% of global IT and business leaders told IDC in a survey in June that their WFH models will likely continue to some degree post-pandemic. The accelerated push to the cloud also can be seen in how enterprises are prioritizing their spending. Synergy Research Group noted that in the second quarter, spending on public cloud infrastructure increased 25%, compared with a 3% decline in spending on data center hardware and software.
GPUs are a key infrastructure technology in the cloud, where they can be used with such modern cloud-based workloads as artificial intelligence (AI) and machine learning, visualization, data science, and analytics. By using Nvidia GPU-accelerated infrastructure through partners, end users can get:
> Access to a broad range of GPUs, from Quadro RTX 6000s for enthusiasts to V100 Tensor Cores for AI, high-performance computing (HPC), and data science workloads.
> Management software to unify private and multicloud infrastructures.
> Services and other offerings to ease cloud adoption and migration.
> Compliance with local data sovereignty laws.
Background: Nvidia for years offered its GPUs for graphic-intensive jobs like gaming, but more than a decade ago expanded the reach of the technology into data centers and then cloud infrastructures, with a focus on such modern technologies as AI and machine learning. Along the way, the Santa Clara, California-based company built up its partner programs to help with the expansion. Nvidia in August added new tools and incentives to its Nvidia Partner Network – which the CSP is part of – which has grown to more than 1,500 members in the past couple of years.
The Buzz: “To cope [with a large remote workforce], enterprises are turning to the cloud as it provides the simplified, flexible management of IT resources that are required to support remote workers, wherever they may be,” Matt McGrigg, director of global business development for cloud and strategic partners at Nvidia, wrote in a blog post. “With Nvidia GPUs and virtualization software, cloud infrastructure can support all kinds of compute and visualization workloads — AI, data science, computer-aided design, rendering, content creation, and more — without compromising performance.”
“As the world continues to adapt to working remote, we see unprecedented demand for high-performance managed desktop as a service across all industries,” said Robert Green, president and CTO of Dizzion. “With innovative Nvidia GPUs, Dizzion cloud desktops enable any global team member to work from home — or anywhere — and keep things business as usual.”
“GPUs and the new era of accelerated computing are powering applications previously thought impossible,” Paperspace COO Daniel Kobran said. “The Paperspace cloud platform provides on-demand GPU processing power behind a unified hub to facilitate collaboration across large, distributed teams for customers such as Medivis, which is using Paperspace to build AI-assisted, real-time analysis to provide surgeons key insights during surgery.”