Nvidia is building out an increasingly complete and ornate set of systems software to run HPC, AI, data analytics, visualization, and now world-simulating applications.
Nvidia has been creating drivers for GPUs for decades, and started building up commercial-grade HPC and AI frameworks, and the libraries and compilers that sit underneath them, a decade and a half ago. And Nvidia’s big acquisition here – big is a measure of importance, not expenditure – was The Portland Group back in July 2013. And since that time, it has built up stacks of HPC and AI frameworks, packaged up neatly in Kubernetes containers, that are the foundation of simulation, modeling, and machine learning applications.
Nvidia acquired Mellanox Technology in March 2019 as much for its networking software – literally the bits but also the expertise embodied in its employees – as for its switch ASICs and network interface cards, and almost immediately it acquired Cumulus Linux in May 2020 for much the same reason. Expertise is more important than any particular configuration of bits we call software. With Mellanox and Cumulus, Nvidia has a deep bench of expertise in interconnects and network operating systems, which complements its own very good SerDes design team and which, among other things, created the NVLink interface and the NVSwitch memory area network – well, that’s what it is, after all – to lash together GPUs into a kind of shared memory SuperGPU.
More recently, Nvidia acquired Bright Computing for its eponymous cluster configuration and management tool, and even more recently Nvidia has pushed out into storage with the rapid-fire acquisitions of distributed block storage provider Excelero and distributed object storage maker SwiftStack. We still think that Nvidia needs high performance file systems if it wants to own a complete stack, and we also think the Excelero and SwiftStack deals were more about getting people than they were about getting any particular piece of software-defined storage. For all we know, Nvidia is going to come up with a file system, with object or block underpinnings, all of its own and tune it for the HPC, AI, and data analytics workloads to chases in the datacenter.
So what else is Nvidia missing in its software stack? Well, a low-level operating system – which of course has to be Linux – to interface between its systems software and the iron, and a high-level operating system – which probably means Kubernetes, but Docker and Hashi Stack are also options – to containerize and pod microservices and denser applications. …
Canonical, which is owned by billionaire Mark Shuttleworth, has put together a very respectable Ubuntu Server distribution of Linux with all kinds of goodies like bare metal and Kubernetes support, and would fit nicely with the Nvidia stack.
But, there are two executives who sell stuff into the datacenter that also see green. One of them, of course, is Jensen Huang, co-founder and chief executive officer at Nvidia and the other one is Melissa Di Donato, chief executive officer at SUSE, the longtime supplier of the enterprise Linux and now a fairly complete Kubernetes platform.
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SUSE is perhaps a better fit than Canonical, and is actually acquirable because after a long line of acquisitions – it has been bought by Novell in 2003, Attachmate in 2010, Micro Focus in 2014, and EQT Partners, a Swedish private equity firm, which bought SUSE for $2.5 billion in 2018. In May 2021, EQT took SUSE public on the Frankfurt Stock Exchange in Germany, raising $1.35 billion and giving SUSE a market capitalization of $6.1 billion at the time.
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Nvidia would not buy SUSE because it needs the revenue stream. At least it doesn’t need it now. But rather Nvidia would do such a deal, with a decent premium over the company’s current $5.1 billion market capitalization, because it wanted a team of 2,400 Linux experts, including engineers and sales people, who could be the foundation of a full Linux-Kubernetes stack for all of the higher level software that Nvidia has already created and even more that it will create in the years to come.
We know about the tight partnership between Nvidia and VMware, and we are well aware that VMware server virtualization is the substrate on a majority of the systems in the enterprise world. And Nvidia is packaging up its software so they can be packaged up to run on the Tanzu variant of Kubernetes running atop the ESXi hypervisor and in conjunction with NSX virtual networking and vSAN virtual storage from VMware. We also know that Nvidia has been working with VMware on its “Project Monterrey” port if the ESXi hypervisor to run on the BlueField family of DPUs from Nvidia. (Three times my brain wanted to type “moneytree” there. . . . Hmmm.)
So what. Nvidia will partner with competitors, as it has been doing for years. It makes servers and it helps others make servers. It can control and optimize its own Linux operating system and Kubernetes distribution while at the same time allowing it to run on Red Hat Enterprise Linux and Ubuntu Server and their respective Kubernetes, or tune it for the Linux distros and Kubernetes container services available on the biggest clouds.
One doesn’t negate the other. But there are obvious advantages in terms of performance, ease of deployment, and pricing control that come from having a complete stack