As demand for AI-based computing grows in India’s capital markets, the National Stock Exchange has deployed a direct-to-chip liquid cooling solution to upgrade its on-premises technology infrastructure. The system supports high-density GPU computing and is designed to scale to 224 GPUs over time, with plans to expand to more than 80 GPUs in the current quarter.
Highlights
- NSE has deployed direct-to-chip liquid cooling infrastructure, launching a scalable, future-ready technology platform for AI deployment.
- NSE will expand its GPU capacity to more than 80 in the current quarter, with the infrastructure designed to scale to 224 GPUs.
- This on-premises solution for AI infrastructure will strengthen data sovereignty, security governance and regulatory compliance, and could soon be extended to the co-location data center.
This article was translated from the original. Read the original version by our correspondent here.
Plans to expand AI computing capacity
According to NSE India, this deployment is a first of its kind in India’s capital markets. It aims to create a scalable, resilient and future-ready technology framework for growing AI workloads. The new cooling infrastructure enables the exchange to deploy GPU-based computing more efficiently in high-density racks.The exchange has already deployed several GPUs and plans to expand this environment to more than 80 GPUs in the current quarter. The infrastructure is designed to scale to 224 GPUs to meet future AI computing needs.
Impact on data sovereignty and market infrastructure
The system has been deployed in NSE’s on-premises data center environment, helping it maintain full control over AI data, computing resources and access. As AI adoption expands across the organization, this framework strengthens data sovereignty and supports alignment with security governance, regulatory expectations and compliance requirements.This initiative is part of NSE’s broader strategy to provide robust, future-ready market technology for Indian market participants. The exchange has said it will also extend DCLC technology to its co-location data center in the near future, based on the needs of market participants.
Our previous report discussed the obstacles facing the expansion of US AI data centers, where rising financing costs, construction delays and power constraints are calling the viability of many projects into question. The article noted that raising capital is becoming more difficult amid high interest rates and inflation, while pressure on the power grid and local opposition are also affecting the pace of expansion.
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