Schneider Electric unveils blueprint for redefining data centres for AI optimisation

The emergence of Artificial Intelligence has sparked substantial transformations and complexities in the planning and management of data centres. With AI applications gaining prominence across various industries, including healthcare, finance, manufacturing, transportation, and entertainment, the requirement for enhanced processing capabilities has also surged. Consequently, data centres must evolve to efficiently cater to the increasing power requirements of AI-driven applications.Schneider Electric, a leader in the digital transformation of energy management and automation, has presented a guide aimed at tackling the challenges in designing physical infrastructure for data centres. This guide is designed to support the evolving landscape of artificial intelligence (AI)-driven workloads and aims to establish the benchmark for AI-optimised data centre design.Projections indicate a substantial growth in AI workloads, with an estimated compound annual growth rate (CAGR) of 26-36% by 2028, leading to heightened power requirements in both existing and upcoming data centres. Addressing this anticipated surge in energy needs involves delving into several key considerations, as outlined in the White Paper, titled “The AI Disruption: Challenges and Guidance for Data Centre Design”. These considerations span four primary physical infrastructure categories: power, cooling, racks, and software tools.Schneider Electric’s latest white paper charts a path for companies to design data centres that are not just capable of supporting AI, but fully optimised for it. The white paper introduces innovative concepts and best practises, positioning Schneider Electric as a frontrunner in the evolution of data centre infrastructure.White Paper 110 is available for download here. “As AI continues to advance, it places unique demands on data centre design and management. To address these challenges, it’s important to consider several key attributes and trends of AI workloads that impact both new and existing data centres,” said Pankaj Sharma, Executive Vice President, Secure Power Division and Data Centre Business at Schneider Electric. “AI applications, especially training clusters, are highly compute-intensive and require large amounts of processing power provided by GPUs or specialised AI accelerators. This puts a significant strain on the power and cooling infrastructure of data centres. And as energy costs rise and environmental concerns grow, data centres must focus on energy-efficient hardware, such as high-efficiency power and cooling systems, and renewable power sources to help reduce operational costs and carbon footprint.”  This new blueprint for organisations seeking to leverage AI to its fullest potential within their data centres, has received welcome support from customers. “The AI market is fast-growing and we believe it will become a fundamental technology for enterprises to unlock outcomes faster and significantly improve productivity,” said Evan Sparks, chief product officer for Artificial Intelligence, at Hewlett Packard Enterprise. “As AI becomes a dominant workload in the data centre, organisations need to start thinking intentionally about designing a full stack to solve their AI problems. We are already seeing massive demand for AI compute accelerators, but balancing this with the right level of fabric and storage and enabling this scale requires well-designed software platforms. To address this, enterprises should look to solutions such as specialised machine learning development and data management software that provide visibility into data usage and ensure data is safe and reliable before deploying. Together with implementing end-to-end data centre solutions that are designed to deliver sustainable computing, we can enable our customers to successfully design and deploy AI, and do so responsibly.”

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