Transitioning to AI-ready data centers

As AI workloads spread, data center operators will need to shift their infrastructure to meet the demands. See the challenges and solutions for introducing AI data centers.

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With the surge of AI and high-compute workloads, data center operators face the challenge and opportunity to reimagine infrastructure

We partner with technology companies and customers in various domains to co-create sustainable AI workload solutions. From power infrastructure to cooling topologies and sustainability consulting, we uniquely support the full spectrum of AI data center needs. As the industry evolves to meet AI demand, Schneider aims to collaborate on inventing new solutions and standard designs for the future.

Challenges of AI data center designs

Densification

Control apps to solve high-density and large computing power needs.

Power availability

Ensuring power capacity to support AI workloads.

Power distribution

Scalability to solve distribution of "big power" in small spaces.

Cooling

Complex liquid cooling systems to solve very high heat output.

Sustainability standards

Balancing the needs of high-density power needs with sustainability standards.

New build or retrofit?

Understand the demand to make decisions on future data center portfolios.

Schneider and NVIDIA partner on AI reference design

Schneider Electric and NVIDIA’s expert teams have partnered to create a comprehensive reference design – one that includes facility power, facility cooling, IT space, and lifecycle software. This reference design will enable customers to prepare their data center infrastructure to embrace the coming technology innovations – whether retrofitting an existing facility or planning a new data center build.

Prepare for next generation cooling

As the data center industry gears up for AI cluster deployment, liquid cooling will be necessary. But how it’s integrated into a comprehensive cooling system design is still up for evaluation and debate. Our latest whitepaper and Innovation Talk webinar are resources to help you understand liquid cooling terminology, the six common heat rejection architectures, and guidance on how to select the best system for your needs.

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Webinar shares guidance on adapting infrastructure

An evolving shift toward higher rack power densities requires adapting data center infrastructure. Watch our webinar on demand to learn the architectural requirements for AI training and inference workloads and hear best practices for addressing concerns with power, cooling, racks, and software.

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Ways to deploy AI data centers

Capitalize on our large training cluster solutions

We enable the creation of large training clusters that maximize processing power and offer high density. Equip workloads with efficient liquid cooling systems and advanced software to manage higher densities and mitigate downtime risk. We also introduce customizable reference designs for up to 100kW per rack.

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Leverage our inference server solutions

We give you a chance to make a lightweight version of the training model. It helps in reducing inference time with an acceptable loss of accuracy. Our solutions improve resiliency and relieve more advanced and slower training models. Because of the Edge architecture, they generate outputs quickly.

Learn more about Edge solutions

Benefits of a dedicated data center for AI

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Computing power

AI-optimized data centers handle large AI computing requirements.

Efficiency

Advanced cooling systems reduce energy consumption and lower costs.

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Scalability

AI capabilities grow with no worry about infrastructure limitations.

Discover our software, products, and services for Data Centers and Networks

Unlock the power of data-driven decisions with our apps, analytics, and services. Gain valuable insights to make smart energy and sustainability choices that will impact your business operations.

DCIM software for data center challenges

DCIM software with a new level of resilience, security, and sustainability.

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Simplified asset management, modeling, and optimization for IT.

MTWO

Integrated 5D BIM construction software for centralized collaboration.

ETAP

Power systems modeling and simulation with digital twin.

Data Center Expert

Real-time monitoring for multi-vendor physical infrastructure.

Manage operations at the edge with real-time monitoring and control on-premise or from the cloud.

EcoStruxure Resource Advisor

Transform energy and sustainability data into actionable insights.

EcoStruxure Power Advisor

Maximize uptime and optimize data with AI-based monitoring.

AVEVA™

Securely visualize and contextualize enterprise-wide operations.

EcoStruxure Building Advisor

Proactively monitor and address building inefficiencies.

From power equipment and cooling to prefab and IT infrastructure, our innovative and connected data center solutions support all environments.

Galaxy UPS

First-class, 3-phase power protection from 10 to 1500kW.

NetShelter Rack PDU Advanced

Best-in-class intelligent rack power distribution for fast, flexible deployment.

Busway and cable management

A complete, flexible line of feeder and plug-in busway lengths and fittings.

Medium-voltage switchgear

High-performance MV switchgear with air, gas, or shielded solid insulation.

Low-voltage switchgear

Our switchboards innovative, easy to install, and built to last.

Prefabricated data center modules

Simplified design and construction to scale capacity quickly.

Hyperpod

Rack-ready system to deploy IT in 8-12 rack increments.

Chillers

Heat rejection for row and room cooling solutions.

In-row cooling

Close-coupled air, water, and glycol cooling solutions.

Discover more about AI data centers

Mitigate downtime risk

AI data centers run at full capacity all the time. High density needs apps to manage and reduce downtime risk.

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Solutions for Cloud and Service Providers

The world’s leading 10 Cloud and Service providers trust Schneider Electric as their partner of choice. Learn more about the solutions we bring to these customers.

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Data center reference designs

Every data center project has its own unique requirements. Documented and validated reference designs facilitate discussions in the early planning phase and are a great starting point for detailed design work.

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Enable AI in data centers

To set up AI data centers, it is necessary to raise data processing power. Learn how to solve imminent issues.

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Get answers on liquid cooling

Get answers to the top seven questions we’ve been asked on liquid cooling.

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Adapt infrastructure to AI

Watch the on-demand Innovation Talk webinar on adapting infrastructure to meet AI requirements.

Prepare for liquid cooling

Watch this Innovation Talk to gain insights into making informed decisions about deploying liquid cooling in your data center.

Partnering for data center AI success

Hear Dion Harris (NVIDIA) and Pankaj Sharma (Schneider Electric) discuss the AI infrastructure revolution and how our partnership is preparing the data center industry.

Discover AI data center design

Get to know challenges and solutions for data center design. See the data for attributes and trends in AI.

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Navigate liquid cooling for AI

Learn about common cooling architectures for liquid cooling and how to select the best system for your AI servers or cluster.

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What is an AI data center?

The AI data center is a facility that stores a network of computing systems and infrastructure that support the high-demanding needs of artificial intelligence (AI) and machine learning applications. The goal of these data centers is to streamline the collection of information and then its processing to efficiently generate responses to prompts entered by the users. The data center for AI needs to have advanced hardware such as graphics processing units, field-programmable gate arrays, application-specific integrated circuits, and many other equipment that optimize the processing and allow for complex computational tasks that are connected to AI operation.

What are AI data center solutions?

Solutions that enable AI-ready data centers encompass numerous technologies, services, as well as strategies that optimize the infrastructure of data centers. The goal is to effectively support both AI and machine learning workloads. AI data center design consists of hardware components in the form of AI-optimized servers as well as storage systems that are adapted to the specific operational conditions in which such systems work. Additionally, AI-specific data centers require top-quality networking equipment as well as software solutions like AI frameworks, libraries, or even development tools that can ensure efficient training, deployment, and then management of AI models.

How can our solutions help you develop your AI data center?

Our solutions, which are specifically designed to accommodate the needs of inference and training workloads, address challenges and requirements of developing, upgrading, and maintaining AI data enters. With our expertise and technology offerings, your business can benefit from optimized hardware and software configurations that are specifically tuned for AI workloads and their needs. Our services also include webinars that can broaden your knowledge of AI data center solutions and show how to enhance your infrastructure and make it scalable, resilient, and energy efficient. Our expertise also includes comprehensive support services, consultation, deployment, and ongoing management of AI data center infrastructure.