Google’s taking the fight to NVIDIA, launches new ARM-based processors to power data centres

Currently, NVIDIA, Intel and AMD dominate the data centre space when it comes to processors. NVIDIA, particularly, has a stranglehold on Data Centres working with AI Models and ML algorithms. However, it seems that Google wants a piece of that action.

At the ongoing Cloud Next, Google announces its new ARM-based processor called Axion. Axion is Google’s first ARM-based CPU that has been specifically created for data centres, which is based on ARM’s Neoverse V2 CPU.

If stats released by Google are anything to go by, Axion performs about 30 per cent better than its fastest general-purpose ARM-based tools in the cloud and about 50 per cent better than the most recent, comparable x86-based Virtual Machines.

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Google also claims that Axion is at least 60 per cent more energy efficient than those same x86-based VMs.

Apparently, Google is already using Axion in services like BigTable and Google Earth Engine and hopes to expand its use in the future.

The release of Axion could bring Google into direct competition with Amazon, which has led the field of ARM-based CPUs for data centres, along with NVIDIA and Ampere. However, if we look at other kinds of processors, Google is going up against Intel and AMD as well.

Amazon’s cloud business, Amazon Web Services AWS, released the Graviton processor back in 2018 and then went on to release the second and third iterations over the following two years. Meanwhile, NVIDIA released its first Arm-based CPU named Grace for data centres in 2021.

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Google started developing their own ARM-based processors years ago but they have mainly been focussed on personal devices like smartphones. The first devices to ship with Google’s ARM-based processor were the Pixel 6 and 6 Pro smartphones back in 2021, which were using a then-new SoC called Tensor.

Ever since then, all Pixel devices have been powered by updated iterations of the Tensor SoC. The Tensor SoC finds its origin with Tensor Processing Units or TPUs, which Google developed to use in their own data centres which they started using in 2015. Google made them available to other parties from 2018 onwards.

Arm-based processors often cost less than regular processors and usually are more energy-efficient options. AI models such as ChatGPT are very resource-hungry and need a ton of electricity and water electricity. Experts estimate that By the end of the decade, AI data centres could consume as much as 20 per cent to 25 per cent of the US’s current power requirements, which isn’t a sustainable model for AI’s development.