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Dell Introduces Concept Astro for AI Workload Optimisation
Dell’s Concept Astro can reduce data centre energy emissions with digital twins
Dell introduces Concept Astro, an AI-powered platform that uses digital twins, automation, and real-time grid data for enterprise AI workloads
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 Concept Astro Platform
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 is a distinguishing feature of Concept Astro. 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.
The Role of Digital Twins
Alyson Freeman, Innovation Lead for Sustainability and ESG at Dell, says: "This capability is exciting but right now just a concept, with our engineers pushing the boundaries of what is possible to deliver at scale." 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.
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. Concept Astro is able to:
- 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
Conclusion
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. Concept Astro is Dell’s approach to future data centre management challenges, addressing the growing power consumption concerns in data centres as AI adoption increases.
By using digital twins, automation technology, and real-time grid data, Concept Astro optimises computational workload scheduling based on energy availability, cost parameters, and operational priorities. The platform has been successfully tested with the Scripps Institution of Oceanography, demonstrating its potential to reduce energy emissions and costs in data centres.
With Concept Astro, Dell is pushing the boundaries of what is possible to deliver at scale, addressing the growing power consumption concerns in data centres as AI adoption increases.