![]() The end result, according to NVIDIA, will be a high-performance and high-bandwidth CPU that is designed to work in tandem with a future generation of NVIDIA server GPUs. Instead, NVIDIA is going their own way by building an Arm server CPU with the necessary NVLink functionality. Previously NVIDIA has worked with the OpenPOWER foundation to get NVLink into POWER9 for exactly this reason, however that relationship is seemingly on its way out, both as POWER’s popularity wanes and POWER10 is skipping NVLink. ![]() The solution to the problem, as was the case even before Grace, is to use NVLink for CPU-GPU communications. In particular, NVIDIA is currently bottlenecked by the use of PCI Express for CPU-GPU connectivity their GPUs can talk quickly amongst themselves via NVLink, but not back to the host CPU or system RAM. NVIDIA’s current server offerings, in turn, typically rely on AMD’s EPYC processors, which are very fast for general compute purposes, but lack the kind of high-speed I/O and deep learning optimizations that NVIDIA is looking for. The company’s GPUs are incredibly well-suited for certain classes of deep learning workloads, but not all workloads are purely GPU-bound, if only because a CPU is needed to keep the GPUs fed. More broadly speaking, Grace is designed to fill the CPU-sized hole in NVIDIA’s AI server offerings. The company isn’t directly gunning for the Intel Xeon or AMD EPYC server market, but instead they are building their own chip to complement their GPU offerings, creating a specialized chip that can directly connect to their GPUs and help handle enormous, trillion parameter AI models. If nothing else, the company is making it clear early on that, at least for now, Grace is an internal product for NVIDIA, to be offered as part of their larger server offerings. The company is offering only limited details for the chip – it will be based on a future iteration of Arm’s Neoverse cores, for example – as today’s announcement is a bit more focused on NVIDIA’s future workflow model than it is speeds and feeds. ![]() With two years to go until the chip is ready, NVIDIA is playing things relatively coy at this time. According to NVIDIA, the chip is being designed specifically for large-scale neural network workloads, and is expected to become available in NVIDIA products in 2023. Dubbed Grace – after Grace Hopper, the computer programming pioneer and US Navy rear admiral – the CPU is NVIDIA’s latest stab at more fully vertically integrating their hardware stack by being able to offer a high-performance CPU alongside their regular GPU wares. Kicking off another busy Spring GPU Technology Conference for NVIDIA, this morning the graphics and accelerator designer is announcing that they are going to once again design their own Arm-based CPU/SoC. ![]()
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