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この演習はコースの一部です
理論を実践に変える、インタラクティブな演習のひとつをお試しください
This module offers an overview of the course and outlines the learning objectives.
This module details the AI Hypercomputer cluster creation process. It covers the key decisions required, including choosing a machine type, consumption option, deployment option, orchestrator, and cluster image.
This module identifies key configuration options and optimization techniques for deploying an AI Hypercomputer cluster on Google Compute Engine (GCE). It covers selecting machine types, accelerator OS images, deployment options, and strategies for optimizing network performance.
This module identifies configuration options for deploying an AI Hypercomputer cluster on Google Kubernetes Engine (GKE). It covers containerization, GKE modes of operation, networking configurations, and workload optimization techniques like distributed training and GPU sharing.
現在の演習
This module examines optimization techniques for architecting an inference workload on GKE. It covers the GKE inference workflow, key infrastructure, and model-level optimizations.
Student PDF links to all modules
