Intel

NVIDIA Buys $5B Worth of Intel, RTX iGPUs Coming to x86, Shared up 25%

NVIDIA and Intel today announced one of the largest industry collaborations in recent years, jointly developing multiple generations of consumer PC and data center products, utilizing the best design teams from both companies. According to the latest announcement, NVIDIA is investing $5 billion at $23.28 per share, making NVIDIA one of Intel's largest shareholders, with a 4.9% stake in the total company. The goal of this collaboration is split into two verticals. One, and perhaps the most interesting one, is the integration of NVIDIA RTX GPUs inside Intel x86 System-on-Chips (SoCs), which Intel's own Arc GPUs previously powered. Intel once even considered tapping AMD with its "Kaby Lake G" design, which never progressed beyond generation one. Now, NVIDIA's RTX GPUs will become the standard for integrated graphics, powering millions of laptops, handheld devices, and possibly even desktop processors.

The second pillar of this collaboration is the development of custom x86 CPUs for NVIDIA, which will be integrated into NVIDIA's AI infrastructure platforms. Spanning multiple verticals such as DGX workstations, HGX servers, and NVIDIA SuperPODs. NVIDIA currently uses a mix of its self-developed Arm-based Grace/Vera CPUs, as well as x86 CPUs in some HGX systems. For now, this has served NVIDIA well, and its data center roadmap indicates that NVIDIA will continue to ship these custom CPUs through its product family. However, with custom x86 CPUs fine-tuned for NVIDIA, Intel will gain significant share in the AI training and inference infrastructure, where NVIDIA previously completely bypassed both x86 vendors with custom Arm designs. For example, Intel's designs, such as Clearwater Forest Xeons, are coming soon with up to 288 "Darkmont" E-cores on a massive chiplet package using the 18A node. This should be a perfect companion for NVIDIA's accelerators, and we could even see some customized versions that offer lower core counts but higher frequencies, all within NVIDIA's SuperPODs with hundreds of GPUs.
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