Forseeing a future dominated by data center-scale computing, Nvidia has moved forward with a huge $6.9 billion purchase of networking vendor Mellanox Technologies. The acquisition is seen broadening Nvidia’s reach in a “broad range of data center scenarios, from enterprise and high-performance computing (HPC) environments to cloud and hyperscale infrastructures.”
Jeffrey Burt contends that the Nvidia’s purchase of Mellanox will create a formidable player in the data center space in this article from eWeek:
“This acquisition … would be transformative for us, changing us from a chip- and system-level company to a data center-level scale company,” Huang said. “In the future we want to optimize data center-scale workloads, again across the entire stack, from the compute node to networking to storage. For this reason, Mellanox’s system-to-system, data center-scale interconnect technology is important to us,” (says Nvidia founder and CEO Jensen Huang).
The broad interest in Mellanox—which offers a broad networking portfolio, from InfiniBand and Ethernet switches to adapters, silicon and software—comes as data center workloads continue to evolve with the rise of such technologies as artificial intelligence (AI), machine learning and data analytics. Data centers are becoming increasingly data-center and compute-needy, putting greater pressure on architectures for more speed and bandwidth, as well as greater power and cost efficiencies.
At the same time, Huang said, Moore’s Law, which has been the driving force behind innovations around CPUs for more than five decades, is beginning to slow. Nvidia a decade ago began offering its GPUs to help accelerate the performance of servers, first in HPC and then in cloud and enterprise data centers, and heterogeneous and accelerated environments will be key to addressing these more modern workloads, he said.
With the growth of AI, analytics and other data- and compute-intensive workloads, organizations will need tens of thousands of server nodes working as a single unit. The network will be the connecting fabric that ties the environment together, said Huang, who several years ago put AI and machine learning at the center of Nvidia’s growth plans.