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Google Cloud Introduced Custom Google Axion Processors for AI Inference Workloads


With Axion, Google Cloud is taking a giant leap forward in preparing its data center for the AI era by embracing greater personalization to boost performance efficiency and expand the capabilities of its general-purpose compute fleet. Axion is built on the Armv9 Neoverse V2. Furthering Google Cloud’s bespoke silicon initiatives, Axion CPUs are engineered to provide clients with enhanced workload performance while minimizing energy consumption.

When it comes to modern demanding workloads and the ever-improving data center infrastructure, custom silicon is the way to go. To tailor our architecture and CPU designs to our partners’ critical workloads, Arm works closely with them. Compared to using older, off-the-shelf processors, Google’s new Axion CPU, which is based on the Arm Neoverse, has better performance, lower power consumption, and more scalability. This makes it a driver of bespoke silicon innovation.

Arm Neoverse is being chosen by cloud providers as a means to optimize their entire stack, encompassing both silicon and software. Custom Google Axion Processors for general-purpose computation and AI inference workloads, built on Neoverse V2, were introduced by Google Cloud. With Axion, you may expect instances with 50% more performance and 60% better energy efficiency compared to similar instances based on current-generation x86.

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Why Does This News Matter?

The performance, efficiency, and innovation flexibility of Arm were the deciding factors for Google Cloud. Integration with existing programs and tools is made much easier with a solid software ecosystem, extensive acceptance in the industry, and interoperability across platforms. Google Cloud has access to a large pool of cloud clients with deployed workloads thanks to Arm. Google has a long history of optimizing Android, Kubernetes, and Tensorflow for the Arm architecture. Our collaboration on initiatives like the SystemReady Virtual Environment (VE) certification and OpenXLA will accelerate the time to value for Arm workloads on Google Cloud, building customer confidence.

As generative AI becomes more accessible to hundreds of millions of users, the world is beginning to absorb the revolutionary changes that AI has the potential to bring to society. Cloud providers are making swift moves to meet the ever-increasing need for artificial intelligence. Because it allows for more computations per watt of power spent, Arm Neoverse is key to this transformation. Compared to older systems built on outdated architectures, AI developers can use trained models on CPU with a third of the energy and in a third of the time. In addition to reducing operational expenses and making better use of computational resources, developers can greatly accelerate inference performance. More efficient designs for generative AI are made possible by Neoverse’s unparalleled flexibility for on-chip or chip-to-chip integration of compute acceleration engines like NPUs or GPUs, which is a trend across the industry.

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1. Enhanced Performance: Axion CPUs offer 50% more performance compared to current-generation x86 processors, boosting computing capabilities significantly.

2. Improved Energy Efficiency: With Axion CPUs, expect 60% better energy efficiency, reducing power consumption and operational costs.

3. Tailored Silicon Innovation: Axion CPUs, based on Arm Neoverse, provide a better performance, scalability, and lower power consumption compared to off-the-shelf processors.

4. AI Readiness: Axion CPUs prepare data centers for the AI era, enhancing performance efficiency and expanding general-purpose computing capabilities.

5. Cloud Service Expansion: Google Cloud’s adoption of Axion CPUs enables the deployment and expansion of various workloads, including AI training and inferencing.

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