Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans

As companies of various sizes adopt graphic processing units (GPU)-based machine learning (ML) training, fine-tuning and inference workloads, the demand for GPU capacity has outpaced industry-wide supply. This imbalance has made GPUs a scarce resource, creating a challenge for customers who need reliable access to GPU compute resources for their ML workloads. When you encounter GPU capacity limitations, you might consider creating on-demand capacity reservations (ODCRs). ODCRs apply to planned, steady-state workloads with well-understood usage patterns.