OCP Advances the Open Data Center Ecosystem Vision at EMEA Summit

The Open Compute Project Foundation turns 15 this year, and at the OCP EMEA Summit, the organization is marking the milestone with an expanding portfolio of work. The catalyst is straightforward: AI infrastructure has made the data center a first-order concern for utility planners, data center operators, and network architects. OCP’s response, formalized last October as the Open Data Center Ecosystem (ODCE) Vision, is an expanded strategic framework that takes its mandate from the power grid all the way down to the silicon die.

The ODCE vision defined three strategic domains — AI data centers, cloud data centers, and the AI computing continuum (focused moving AI inference closer to end users) — across a technology scope spanning facilities and physical infrastructure, IT infrastructure, and systems management. The six months since have produced concrete work across all three.

Rethinking the Facility: Power, Physical Design, and Secure Data Exchange

On the facilities side, three efforts address the physical and operational foundations of next-generation AI data centers. The first is a new white paper that examines how data center facilities can be updated for direct current (DC) power distribution and provides an overview different power distribution architectures. It examines not only key design concepts, but tradeoffs across power conversion, energy storage integration, and regulatory considerations. The work is designed to build shared vocabulary among data center operators, equipment manufacturers, utilities, and power authorities, stakeholders who have historically operated in separate technical communities.

Second, an Open Data Center Roadmap contributed by Google identifies design principles for next-generation machine learning (ML) infrastructure. The design details physical interface specifications based on Google’s tensor processing unit (TPU) deployments that are expandable to industry GPUs, starting a collaborative workstream. It covers hot aisle containment, cable conveyance, power diversity tiers, and thermal management to support mega-scale ML hardware deployments.

The third tackles a subtler but increasingly critical problem: secure data exchange between operational technology and IT systems. As AI workloads demand real-time coordination across power, thermal, and mechanical systems, data from building management and power monitoring infrastructure must cross sensitive boundaries. An IT↔OT telemetry contribution proposes a zero-trust framework and standardized protocol for that exchange, enabling coordinated load shedding, real-time incident response, and end-to-end power usage effectiveness (PUE) optimization that current methods cannot support.

Inside the Data Hall: Open Networking at Scale

Two initiatives that address distinct networking challenges in AI cluster infrastructure are among the key outputs the community is highlighting at this spring’s summit. ESUN (Ethernet for Scale-Up Networking) released a base specification designed to improve efficiency, latency, and reliability to meet the demands of scale-up GPU connectivity. The specification evolves standard Ethernet for large GPU domains by replacing IP headers with a compact ESUN header, using media access control security (MACSec) at Layer 2, and treating all accelerators in a domain as a single logical GPU. The result is reduced idle compute time and faster end-to-end training and distributed inference. Let by Meta and Microsoft, more than 40 companies contributed to the base specification, and discussion for the next version is already underway.

Open Cluster Design, meanwhile, addresses the challenge of scale-out networking through the lens of cluster design. This strategic initiative addresses the fact that the majority of AI network implementations today are one-off designs. It aims to produce complete, procurement-ready system architectures to give operators a reusable technical foundation. White papers and reference architectures released this spring introduce the concepts of open pods and open clusters composed of open pods, allowing for modular cluster design. Broadcom and Celestica are among early contributors.

Beyond the Data Hall: Bringing Inference to the Edge

Finally, OCP’s AI Computing Continuum initiative, focused on bringing inference closer to end users, has made meaningful progress on multiple fronts. The project has established an alliance with the IOWN (Innovative Optical and Wireless Networks) Global Forum. It has launched sub-projects examining how to bring AI-native servers to edge data centers and at wireless open hardware for 6G wireless access. An AI-enabled open radio unit (O-RU) Experience Center developed with NVIDIA, Lattice Semiconductor, and University of New Hampshire recently opened as well, with details available in OCP’s Marketplace.

The TechArena Take

OCP has historically been strongest at the rack. What the ODCE Vision represents is a deliberate move to make OCP structurally relevant at every layer of the AI infrastructure stack, and the EMEA Summit in Barcelona this week is where much of that work goes on display. The Summit brings together global technical leaders to tackle data center sustainability, energy efficiency, and heat reuse, themes that sit squarely at the intersection of OCP’s expanded mandate and the region’s energy priorities. A marketplace with more than 160 solution providers and the announcement of diverse new members, including OpenAI, Crusoe, ABB, and Trane Technologies, signal how broad the OCP tent has become. For anyone tracking where open infrastructure standards are headed, Barcelona this week is the place to be.