Nvidia,Qualcomm,ARM,NXOI know I've been told on this site that these companies don't work together. Qualcomm is not a think tank so I've been told. Oh, did mention the definition of Ecosystem? Is Nvidia going to buy ARM? Would that be strategic? Would it be nice to have a foothold in Asia as Korea and Tiawan are moving 5G and AI like there is no tomarrow? I've been beaten up by mentioning any of this. Told it was hog wash: that I was slow and easy not that I was taking it slow weighing my options and easing in for the kill.
Where Arm comes inBut Nvidia has one competitive barrier remaining that prevents it from complete domination of the data center ecosystem: It has to interoperate within the Wintel ecosystem because the CPU architecture in data centers is still x86, whether from Intel or AMD.Arm’s server chips market share is still minute, but it has been extremely successful. And, with TSMC as a manufacturing partner, it is rapidly overtaking Intel in raw performance in market segments outside of mobile phones. But Arm’s weakness is that the hardware-software ecosystem is fragmented, with Apple and Amazon having a mostly proprietary software approach and smaller companies such as Ampere and Cavium being too small to create a large industry ecosystem comparable to Wintel.Nvidia and Arm announced in June that they will work together to make Arm CPUs work with Nvidia accelerators. First of all, this collaboration gives Nvidia the ability to add computing capabilities to its data center business. Secondly, and more importantly, it puts Nvidia in a strong position to create a hardware-software ecosystem around Arm that would be a serious threat to Intel.The coming shiftThe reason such a partnership is particularly important today is because the computer industry is going through its next strategic inflection point. This new tectonic shift will have major repercussions for the industry and the competitive landscape. And if historical trends continue, a merged Nvidia/Arm would result in a market at least 10 times larger than today’s mobile phone or cloud computing market. It is an understatement to say that the stakes are huge.There are several forces driving this new shift. One is the emergence of faster 5G networks that are designed to support a far larger number of devices. One of the key features of 5G networks is edge computing, which will put high-performance computing right at the very edge of the network, one hop away from the end-device. Today’s mobile phones are still tied to a descendant of the old client-server architecture established in the ’90s with networked PCs. That legacy results in high latency networks, which is why we experience those annoying delays on video calls.Next-generation networks will have high-performance computers with parallel accelerators at the very edge of the network. The endpoints — including autonomous vehicles, industrial robots, 3D or holographic communications, and smart sensors everywhere — will require a much tighter integration with new protocols and software architectures. This will achieve much faster, and extremely low latency communications through a distributed computing architecture model. The amounts of data produced — and needing processing — will increase by orders of magnitude, driving demand for parallel computing even further.Nvidia’s roadmapNvidia has already made its intentions clear that cloud-to-edge computing is on its roadmap:“AI is erupting at the edge. AI and cloud native applications, IoT and its billions of sensors, and 5G networking now make large-scale AI at the edge possible. But it needs a scalable, accelerated platform that can drive decisions in real time and allow every industry to deliver automated intelligence to the point of action — stores, manufacturing, hospitals, smart cities. That brings people, businesses, and accelerated services together, and that makes the world a smaller, more connected place.”Last year Nvidia also announced that it is working with Microsoft to collaborate on the Intelligent Edge.This is why it makes strategic sense for Nvidia to buy Arm and why it would pay a very high price to be able to own this technology. Ownership of Arm would give Nvidia greater control over every aspect of its ecosystem with far greater control of its destiny. It would also eliminate Nvidia’s dependence on the Intel compute stack ecosystem, which would greatly increase its competitive position. By owning Arm instead of just licensing it, Nvidia could add special instructions to create even tighter integration with its GPUs. To get the highest performance, one needs to integrate the CPU and GPU on one chip, and since Intel is developing its competing Xe line of accelerators, Nvidia needs to have its own CPU.Today Nvidia leads in highly parallel compute and Intel is trying to play catch-up with its Xe lineup. But as we have learned from the PC Wintel days, the company that controls the ecosystem has a tremendous strategic advantage, and Nvidia is executing well to position itself to become the company that will be the dominant player in the next era of computing. Nvidia has a proven track record of creating an impressive ecosystem around its GPUs, which puts it in a very competitive position to create a complete ecosystem for edge computing including the CPU.