Advanced

Training Cluster Design at 10k GPUs

Size a training cluster from the model, data and completion deadline. Then check the network, storage, power and recovery capacity needed to keep those GPUs productive.

This concept is part of Premium, which includes all concepts, course lessons and answers.

Get Premium · ₹2,000 / $256 months of access · one payment · no auto-renew

RELATED CONCEPTS

Rail-Optimized and Fat-Tree Fabrics Topology-Aware Scheduling Checkpoint I/O Power and Datacenter Constraints Training Uptime and Interruption Statistics GPU Job Scheduler Design

PRACTICE THIS IN REAL QUESTIONS

AI Infrastructure System DesignDesign a training cluster for 10,000 GPUs: pods, fabric, storage, failure domains and the scheduler. Justify every number.→Hardware, Cabling & Cluster Build-OutYou have budget for roughly 1,000 GPUs and a greenfield site. Specify the cluster.→AI Infrastructure System DesignDesign a training cluster for a one-trillion-parameter MoE. Size it, choose the parallel layout, and map it onto the fabric.→Networking, Interconnects & StorageDesign the complete network for a 1,024-GPU cluster: compute fabric, storage, management. What are the counts and where does the money go?→Hardware, Cabling & Cluster Build-OutYou have exactly 1 MW of facility capacity. Maximize training throughput.→GPU & Accelerator ArchitectureDesign a non-blocking network fabric for 512 H100s. How many switches, how are they wired, and where does the NVLink domain end?→