Examples
Worked examples
- Is an instance
A research workflow queues simulation jobs to run when forecast UK grid intensity drops below 200 g CO2e per kWh.
- Is an instance
A cluster job scheduler offers a low-carbon queue with priority drop in exchange for delayed start.
Counter-examples
Looks similar, but isn't
- Not an instance
Running interactive notebook sessions on a high-carbon grid is unavoidable and not in scope.
- Not an instance
Marketing 'green' compute without runtime carbon-intensity sensing is not carbon-aware.
Editorial commentary
Carbon-aware computing builds on the observation that grid carbon intensity varies by region and by hour, sometimes by more than 5x. Tools like the Carbon Aware SDK (Green Software Foundation) and Electricity Maps API expose real-time and forecast carbon intensity. Implementations include time-shifted batch jobs, region-shifted training (subject to data-sovereignty rules), and demand-response queues that pause when intensity spikes. The technique is most effective for non-urgent, interruptible workloads typical in research compute.
References
- Green Software Foundation Carbon Aware SDK; Electricity Maps API documentation.
Also known as
Carbon-aware scheduling · Grid-aware computing
Machine-readable encodings
Use in your systems
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