GPU servers are extremely expensive, especially those with high-end NVIDIA GPUs like the A100, H100/H200, and GB100. To make AI/ML training more efficient, these resources should be fully utilized to their maximum potential.
Federator.ai GPU Booster integrates with NVIDIA’s high-end GPUs using Multi-Instance GPU (MIG) technology, which splits a GPU into smaller instances with completely isolated memory and compute cores. This capability to manage both physical and logical GPUs enables Federator.ai GPU Booster to enhance GPU utilization with the most resource-efficient MIG instance configurations for the GPU cluster by up to 90%.
Visibility for Efficient GPU Resource Configuration
View both physical GPUs with detailed utilization and memory metrics, along with logical GPUs in various configurations. Track each type of logical GPU requested to ensure they are ready for allocation to different workloads.
High Quality of Service for MultiTenant AI Training
Leverage MIG to provide high QoS due to the isolation of resources for each GPU instance, effectively eliminating resource interference or competition among AI applications.
Recommendations for Efficient GPU Resource Configuration
Provide detailed configuration recommendations for each GPU server to efficiently accommodate dynamic workloads and significantly enhance overall utilization.