Schneider Electrical and ETAP, the trade and know-how chief in energy system design and operation, are unveiling a cutting-edge digital twin that may precisely design and simulate the facility wants of AI Factories. Leveraging the NVIDIA Omniverse™ Blueprint for AI manufacturing unit digital twins, Schneider Electrical and ETAP allow the event of digital twins that convey collectively a number of inputs for mechanical, thermal, networking, and electrical methods to simulate how an AI Manufacturing unit operates. The collaboration is ready to remodel AI Manufacturing unit design and operations by offering enhanced perception and management over {the electrical} methods and energy necessities, presenting a possibility for vital effectivity, reliability and sustainability features.
Whereas primary visualization {of electrical} methods was beforehand doable, the mixing of ETAP and NVIDIA Omniverse applied sciences permits the creation of a complete AI Manufacturing unit digital twin the place a number of dynamics work together seamlessly. ETAP’s subtle modeling know-how will create a digital reproduction of a knowledge middle’s electrical infrastructure and mix it with real-time energy system information, superior analytics, and insights. Clever algorithms analyze and predict energy consumption and distribution patterns, permitting unprecedented insights into:
● Superior electrical system design and simulation
● Dynamic “What-If” situation evaluation
● Actual-time electrical infrastructure efficiency monitoring
● Superior vitality effectivity optimization
● Predictive upkeep and system reliability evaluation
● Infrastructure wants based mostly on energy utilization that may assist cut back whole price of possession
From large-scale coaching clusters to edge inference servers, AI workloads are driving a major enhance in information middle energy consumption. Not like conventional computing duties, AI operations — notably mannequin coaching and complicated inference processes — require substantial computational energy, resulting in larger rack energy densities. As AI adoption accelerates, startups, enterprises, colocation suppliers, and web giants should rethink information middle design and administration to handle the rising want for energy effectivity.
ETAP and NVIDIA’s collaboration introduces an modern “Grid to Chip” method that addresses the important challenges of energy administration, efficiency optimization, and vitality effectivity within the period of AI. Presently, information middle operators can estimate common energy consumption on the rack degree, however ETAP’s new digital twin goals to extend precision on modeling dynamic load conduct on the chip degree to enhance energy system design and optimize vitality effectivity.
This collaborative effort highlights the dedication of each ETAP and NVIDIA to drive innovation within the information middle sector, empowering companies to optimize their operations and successfully handle the challenges related to AI workloads. The collaboration goals to reinforce information middle effectivity whereas additionally bettering grid reliability and efficiency.
“As AI workloads develop in complexity and scale, exact energy administration is important to making sure effectivity, reliability, and sustainability,” mentioned Dion Harris, Senior Director of HPC and AI Manufacturing unit Options at NVIDIA. “By our collaboration with ETAP and Schneider Electrical, we’re providing information middle operators unprecedented visibility and management over energy dynamics, empowering them to optimize their infrastructure and speed up AI adoption whereas enhancing operational resilience.”
“This collaboration represents greater than only a technological answer,” mentioned Tanuj Khandelwal, CEO of ETAP. “We’re essentially reimagining how information facilities may be designed, managed, and optimized within the AI period. By bridging electrical engineering with superior virtualization and AI applied sciences, we’re creating a brand new paradigm for infrastructure administration.”
Pankaj Sharma, Government Vice President for Information Facilities, Networks & Providers at Schneider Electrical added, “Collaboration, pace, and innovation are the driving forces behind the digital infrastructure transformation that’s required to accommodate AI workloads. Collectively, ETAP, Schneider Electrical, and NVIDIA should not simply advancing information middle know-how — we’re empowering companies to optimize operations and seamlessly navigate the facility necessities of AI.”
