Hewlett Packard Enterprise (HPE) today announced that it has been chosen to power the Edinburgh International Data Facility (EIDF), Europe’s first regional data innovation center at the University of Edinburgh EPCC in Scotland. HPE will deliver an end-to-end infrastructure featuring its industry-leading high-performance computing (HPC) and artificial intelligence (AI) solutions powered by HPE Apollo Systems and HPE Superdome Flex Servers, as well as HPE Ezmeral Container Platform software capabilities.
The deal, which has an expected value of more than US $125 million over 10 years, will help 1,000 public, private and non-profit organizations to develop products and services using R&D and other data-driven programs, with a long-term vision to establish the Edinburgh region as the Data Capital of Europe.
As a hub for innovation, the EIDF will enable R&D on initiatives focused on addressing global issues such as food production, climate change, space exploration and genetically-tailored healthcare. The EIDF will offer researchers access to HPC and AI technologies to apply analytics to modeling and simulation to increase accuracy of results and speed time-to-discovery.
The EIDF will also improve overall insights by allowing users to securely access shared datasets and analytics from public and private sources.
The EIDF will play a critical role in the region’s Data Driven Innovation (DDI) program, which involves greater collaboration between industry, the public sector and academia. The new facility will power five DDI hub sites with vital infrastructure to meet complex long-term project demands. The DDI program was pioneered by the University of Edinburgh, along with Herriot Watt University, to tackle societal and industrial challenges and deliver benefits from the data economy, while improving the digital and data skills of over 100,000 people from across the region.
“We are pleased to be working with HPE to deliver what we believe is the only facility of its kind in Europe focused specifically on data-driven regional growth,” said Mark Parsons, Director of EPCC at the University of Edinburgh. “With the Edinburgh International Data Facility, we are combining computing and data resources to create a facility that will allow organizations to use data to innovate throughout their organizations. HPE is uniquely positioned to provide the spectrum of infrastructure and services, as well as the flexibility that this project demands.”
To support its mission, EIDF turned to HPE to uniquely deliver an end-to-end infrastructure that seamlessly combines advanced HPC, AI, container, and software technologies into a single framework to enable collaborative, optimal experiences across broad groups of users.
As AI and ML practices are becoming integral to scientific research and engineering, managing AI workloads and applications at scale is a critical requirement for EIDF. In order to address these requirements, EIDF is deploying the HPE Ezmeral Container Platform running on HPE Apollo Systems that are purpose-built to support HPC, deep learning and other data-intensive workloads. Additionally, the platform will also run HPE Superdome Flex Servers to support applications requiring large in-memory processing.
The HPE Ezmeral Container Platform provides native Kubernetes support and enables self-service AI / ML applications for EIDF scientists, with flexible use of accelerators such as GPUs. It will also allow developers to standardize machine learning workflows and accelerate AI deployments from months to days with the HPE Ezmeral ML Ops solution. The solution enables developers to streamline and speed up the entire machine learning model lifecycle from proof-of-concept and pilot stages, all the way through deployment, using a DevOps-like process to standardize models.
It also includes pre-integrated persistent data storage in the form of the HPE Ezmeral Data Fabric file system, for high-performance and high-throughput advanced analytics. This allows EIDF scientists to easily access the data they need in a secure multitenant and collaborative manner, accelerate the deployment of machine learning workloads and models, and get to insights faster.
HPE will also deliver the Cray Shasta ClusterStor E1000 system, which utilizes tailored software and hardware features to meet high-performance storage requirements of any size. It is purpose-built to support EIDF’s ongoing data growth and converged HPC and analytics workloads using intelligent data management. EIDF will gain 20 petabytes of storage capacity with the new system which will be used for the regional data facility and for vital COVID-19 research at the University of Edinburgh.
“HPE is proud to embark on this long-term initiative with the University of Edinburgh, following a highly competitive tender process,” said Lee Rand, Director of high-performance computing and artificial intelligence at HPE EMEA. “We were chosen due to the flexibility and reliability offered through our end-to-end solutions portfolio, and because we were one of the very few organizations able to seamlessly combine all of the Edinburgh International Data Facility’s requirements into a single framework. In the data-centric era deriving insights and value from across multiple datasets will be a key to success for business and government alike. We look forward to boosting the UK’s capacity for data-driven innovation through this initiative.”
Shipment and installation are planned to begin immediately, with first orders already underway. The agreement is for a single source framework through to 2030, with the EIDF expected to be fully operational in the fall of 2020.
About Hewlett Packard Enterprise
Hewlett Packard Enterprise is the global edge-to-cloud platform-as-a-service company that helps organizations accelerate outcomes by unlocking value from all of their data, everywhere. Built on decades of reimagining the future and innovating to advance the way we live and work, HPE delivers unique, open and intelligent technology solutions, with a consistent experience across all clouds and edges, to help customers develop new business models, engage in new ways, and increase operational performance. For more information, visit: www.hpe.com.