The challenge
Datacenters must decide when newer hardware’s efficiency gains justify the cost and embodied carbon of manufacturing a replacement. Refresh too early and useful equipment is retired prematurely. Refresh too late and inefficient systems continue consuming energy and money. A single fleet-wide server cadence also ignores that accelerators, processors, memory, and storage improve at different rates—and that electricity prices and grid carbon vary by location.
The work
TechRefresh is a joint collaboration with the University of Pennsylvania and Google that turns this tradeoff into an explicit, reproducible optimization problem. Its open-source framework can compare financial, carbon, or jointly priced objectives; model multiple replacements over a planning horizon; and evaluate whole-system or component-level refresh policies.
The accompanying research pipeline connects public hardware, energy, and carbon data to fitted component trajectories, scenario definitions, sensitivity analysis, and manuscript figures. Assumptions remain configurable so conclusions can be tested against different growth rates, accounting boundaries, locations, and carbon prices.
Why it matters
Hardware refresh is usually treated as an accounting convention or procurement cycle, even though it is also a sustainability decision. TechRefresh makes the competing costs visible and gives operators a common framework for asking when replacement is justified, which components should share a cadence, and when local energy and carbon conditions should change the plan.
The result is decision infrastructure rather than a universal schedule: a transparent way to compare policies, expose the assumptions driving them, and avoid shifting environmental burden between manufacturing and operation without noticing.