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NSE deploys liquid cooling technology for AI infrastructure, targets 224-GPU capacity

The deployment is aimed at supporting high-density GPU-based computing through a scalable cooling architecture.

NSE deploys liquid cooling technology for AI infrastructure, targets 224-GPU capacity

The National Stock Exchange (NSE) is set to bolster its artificial intelligence (AI) computing infrastructure by deploying liquid cooling technology, aiming for a capacity of up to 224 graphics processing units (GPUs). This move is part of NSE's strategy to meet growing AI workloads and future computing demands. The exchange has already installed multiple GPUs and plans to increase the capacity to over 80 GPUs within the current quarter.

The on-premises data center, designed for high-density GPU racks, can support up to 224 GPUs, providing ample room for further expansion as NSE scales its AI applications. The deployment is intended to address the increasing power and cooling demands of AI applications, thereby enhancing data sovereignty by enabling full control over AI data, computing resources, and access.

This aligns with NSE's commitment to security governance and compliance with regulatory requirements as AI adoption continues to expand. Viral Mody, NSE's Executive Director, emphasized the company's investment in advanced technologies to improve operational excellence, efficiency, and resource utilization. The DCLC technology deployment, as described by Chief Technology Officer Sampath Manickam, offers a scalable and energy-efficient foundation for high-density GPU computing, positioning NSE for the next generation of AI workloads.

NSE intends to extend the liquid cooling technology to its co-location data center in the near future, based on market participants' requirements. This initiative aligns with NSE's broader goal of creating resilient and scalable technology infrastructure to support the evolving needs of India's capital markets.

Written by urgent.news from Hindu BusinessLine's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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