Graphics processing unit (GPU) clusters in modern artificial intelligence (AI) environments generate power variations from idle to full load in milliseconds, creating significant stress on the current power infrastructure from the grid to the data center facility itself. How can data centers maintain reliable power protection while supporting demanding AI workloads?
Two breakthrough uninterruptible power supply (UPS) control features now enable precise management of these challenging load patterns:
- Battery Shield: Actively prevents unnecessary battery cycling during AI workload transients. This innovative feature enables the UPS to absorb power steps ranging from 0% to 100% internally and mitigate power steps exceeding 100%, thereby protecting batteries from micro-discharges that accelerate equipment aging. The result: longer battery life and guaranteed energy reserves for true outage events.
- Input Power Smoothing (IPS): Transforms UPS batteries into an intelligent power buffer that filters AI workloads. In dynamically absorbing or injecting power, IPS maintains a stable input profile despite extreme variations in AI load on the UPS output generated by GPU clusters. This protects upstream infrastructure and enables reliable generator operation, critical for large-scale AI deployments.
This technical white paper provides:
- Detailed algorithms and operational principles of advanced AI control features
- Real testing data from AI workload simulations
- UPS and battery sizing considerations for optimal performance with AI workloads
- Implementation best practices
Validated benefits from these technologies include:
- Reduction in battery micro-cycling
- Input power variation control
- Consistent input power smoothing with proper battery sizing
- Compatible with multiple battery technologies
- Configurable parameters for site-specific needs
Whether you're designing new AI infrastructure or optimizing existing facilities, this technical guide can help data center designers and operators understand how advanced UPS firmware can solve the unique power challenges of AI computing.
