Sustainable computing for HPC and AI

A single large-scale CFD simulation running 500 hours can generate 10,000 tons of CO₂, equivalent to flying a Boeing 777 from New York to Beijing and back. That's the lifetime emissions of 240 gas-powered cars.

Meanwhile, global data center energy consumption is doubling by 2026. AI is driving the surge and most organizations have no idea how much their workloads actually cost to run.

Reduce emissions and cut costs with proven strategies

Understand HPC's carbon footprint and discover why simulation is both the problem and the solution. AI's energy appetite matters more than you think, especially when inference often costs more than training. Google's own data reveals the true expense of running these workloads at scale.

Get practical optimization strategies you can implement immediately. GPU-aware scheduling, smart hardware selection, cloud bursting, and workload consolidation aren't just theoretical concepts, they're proven ways to cut costs and emissions.

Learn how to measure and monitor power consumption so improvements can be tracked and verified. Cut operational costs, improves performance per watt, and scale up without scaling your energy bill.

Download the e-book to explore how Siemens solutions are built to manage large-scale workloads while keeping your carbon footprint in check.