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Kao Data Becomes NVIDIA DGX-Ready, Establishing the UK Innovation Corridor's Home for HPC and AI


News provided by

Kao Data

25 May, 2021, 09:00 GMT

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- NVIDIA DGX-Ready status enables Kao Data to support and host the latest NVIDIA accelerated computing technology

- Provides a dedicated technical environment for start-ups, scale-ups and world-leading organisations utilising GPU-accelerated computing on an industrial-scale

- Architectural requirements of its OCP-Ready™ facility provides seamless integration with NVIDIA DGX systems, and establishes a home for HPC and AI within the UK Innovation Corridor

LONDON, May 25, 2021 /PRNewswire/ -- Kao Data, the specialist developer and operator of advanced, carrier neutral data centres for high performance colocation, has today announced it has become NVIDIA DGX-Ready Data Center certified. This step further reinforces its capabilities as a world-class data centre operator and highlights its expertise in delivering customised architectures for high-performance computing (HPC), AI and supercomputing environments.

The DGX-Ready Data Center status officially certifies Kao Data's capability to support and host the latest breakthroughs in NVIDIA GPUs such as the NVIDIA A100 Tensor Core GPU, an area in which the organisation is seeing increased adoption through its work with customers in Cambridge and the UK Innovation Corridor. This also includes NVIDIA's DGX SuperPOD, which provides the digital foundations for comprehensive advances in machine learning and deep learning technologies.

"DGX-Ready Data Center architectures are quickly changing both the dynamics and capabilities of data centres built for HPC, AI and supercomputing," said Gérard Thibault, CTO, Kao Data. "From inception, Kao Data was precision engineered to deliver a dedicated, robust and resilient environment for intensive computing. Whether a solo DGX system, or something far larger like the acclaimed NVIDIA Cambridge-1 supercomputer, Kao Data is the perfect home for these forms of advanced computing."

Designed to be ultra-energy efficient, Kao Data offers a design Power Utilisation Effectiveness (PUE) of 1.2 and provides data halls with concrete slab-flooring, wide containment aisles, and no columns. Kao Data allows data halls to be customised to suit air-cooled HPC architectures with various rack power densities. NVIDIA customised Kao Data's power and cooling infrastructure to easily accommodate a DGX A100 SuperPOD deployment, such as the NVIDIA Cambridge-1, which is expected to rank among the world's top 5 most energy-efficient supercomputers on the Green500 list, being both efficiently cooled and powered by renewable energy.

"Cambridge and the UK Innovation Corridor is a transformative technology hub, and a significant growth region for HPC and AI," said Marc Hamilton vice president of solutions architecture and engineering at NVIDIA. "Having a DGX-Ready Data Center partner such as Kao Data within this digital ecosystem is a crucial step that reinforces our customer commitments and supports them throughout the journey."

For more information visit kaodata.com.

About Kao Data

Founded in 2014, Kao Data develop and operate advanced data centres for high performance colocation. From our hyperscale inspired campus in the heart of the UK Innovation Corridor between London and Cambridge - we provide cloud, HPC, AI and enterprise customers with a world-class home for their compute.

Our Harlow campus - built on the site of Sir Charles Kao's pioneering discovery of fibre optic cable in 1966 - is a development of four state-of the-art, OCP-Ready™, carrier neutral data centres. When fully completed the 15 acre, +£230m campus will support an ITE load of over 40MW, across 150,000sq ft of technical space – all powered by 100% renewable energy.

Backed by Legal & General and Goldacre - Noé Group, Kao Data is one of the largest campus developments in the UK and represents the future in sustainable, efficient and scalable computing - providing an industry blueprint to develop further best-in-class data centres.

kaodata.com

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