As tech giants rush to join the resource-intensive AI rivalry and ESG regulations become stricter across different regions, the burgeoning environmental impact has gained increased attention from AI trainers and data center operators.
Federator.ai GPU Booster provides visibility into environmental metrics, such as power consumption and temperature, for each GPU device, helping trainers and data centers maintain GPU server health. Cooling metrics, a significant part of power usage, will soon be added to further minimize the environmental impact of AI/ML training.
Visibility into Environmental Metrics
Cover not only the workloads distributed to each GPU but also the power consumed and temperature generated by each GPU, helping trainers monitor performance and avoid downtime during training.
Cooling Integration with GPU Servers
Integrate with popular GPU servers’ air and liquid cooling systems, using workload-pattern predictions to reduce cooling power and extend GPU server lifespan.
Fault Tolerance Enhancement
Provide fault prediction and detection to maintain operation despite failures, ensuring no delays in AI/ML training jobs and gaining a competitive edge in the pursuit of AGI.