Dell Introduces Concept Astro for AI Workload Optimisation
The exponential growth of AI is creating an energy crisis that threatens to undermine the technology's potential.
This surge comes as technology firms deploy thousands of new GPU clusters across global markets, each requiring substantial power and cooling infrastructure.
Hyperscale computing providers report facing unprecedented constraints on data centre expansion, with the availability of reliable grid connections now often determining site selection rather than traditional factors such as fibre connectivity or labour markets.
In financial terms, energy costs now represent between 40-60% of total data centre operational expenditure, according to research firm Gartner, placing pressure on margins throughout the technology sector.
In response, Dell Technologies has unveiled a new system designed to address these growing power consumption concerns in data centres as AI adoption increases.
The company's Concept Astro platform uses AI, digital twins and automation technology to optimise computational workload scheduling based on energy availability, cost parameters and operational priorities.
Digital twin simulation for workload optimisation
The Concept Astro platform is Dell's approach to future data centre management challenges.
The system utilises agentic AI to forecast computational requirements for specific workloads.
The platform incorporates real-time electricity grid data and forecasts to identify optimal moments, locations and computational resources for running jobs.
It can also prioritise workloads based on business requirements, energy availability and cost considerations.
The system provides users with dashboards and reports customised for different roles within an organisation, from research teams to financial officers, delivering operational insights and recommendations.
“This capability is exciting but right now just a concept, with our engineers pushing the boundaries of what is possible to deliver at scale,” says Dr Alyson Freeman, Dell's Innovation Lead for Sustainability and ESG.
“In this iteration, we're using digital twins to simulate workloads so we can extract insights and identify ways to use available data centre power more effectively with power grid awareness,” Alyson explains.
The platform builds upon Dell's existing AI operations monitoring suite and incorporates features from the company's AI operations assistant, including capabilities for users to ask context-specific questions about connected infrastructure and receive recommendations based on current system configurations.
Dell Concept Astro demonstrating cost reduction
The development of Concept Astro responds to challenges created by the resource-intensive nature of AI workloads, which require substantial computational capacity and corresponding energy inputs to operate effectively.
- Forecast the time and energy required for specific workloads
- Pull in real-time grid data and forecasts to identify optimal moments, locations and resources for running jobs
- Prioritise workloads based on business needs, energy availability and cost
- Offer users a dashboard and custom reports tailored to roles from researchers to CFOs, providing actionable insights and recommendations
As AI-driven applications proliferate across industries, data centre operators face increasing pressure to balance performance requirements with energy constraints, variable costs and sustainability targets.
This means that securing reliable and cost-effective energy has become a primary concern for data centre managers.
“We're pushing ourselves to continually innovate, refine and enhance our offerings to deliver even greater business and societal value. What drives us is helping our customers overcome their biggest challenges,” Alyson says.
The role of digital twins
A distinguishing feature of Concept Astro is its implementation of digital twin technology.
By creating virtual models of data centre operations, the system can simulate workloads and energy consumption patterns, enabling the extraction of operational insights to maximise power utilisation and adapt to changing grid conditions
To assess Concept Astro's capabilities in real-world conditions, Dell established a partnership with the Scripps Institution of Oceanography at the University of California San Diego, an oceanographic research centre that processes substantial volumes of underwater imagery.
The institution processes approximately 350GB of data per dive, with 300 to 400 dives conducted annually, to generate high-resolution three-dimensional models for coral reef research.
This work requires significant computing and data storage resources.
During the pilot implementation, Concept Astro enabled Scripps to schedule image processing during optimal energy windows, reducing strain on the electrical grid.
The institution achieved 20% cost savings and a 32% reduction in emissions according to Dell.
Processing throughput doubled after upgrading to Dell's AI infrastructure with Nvidia processors.
Megan Carrasco-Beyer, Senior Consultant Global Portfolio Sustainability Marketing Lead at Dell, says: “I am so excited to share the project we've been working on for nearly two years.
“Concept Astro is Dell Technologies' vision for the future of efficient data centre operations. We worked with the Scripps Institution of Oceanography, part of UC San Diego, to pilot this concept and they are already seeing great results.”
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