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Cloud TPU
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Overview
Guides
Reference
Samples
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Overview
Guides
Reference
Samples
Support
Resources
Cross-product tools
More
Console
Discover
Introduction to Cloud TPU
TPU architecture
TPU software versions
TPU versions
TPU7x (Ironwood)
TPU v6e
TPU v5p
TPU v5e
TPU v4
TPU v3
TPU v2
Regions and zones
JAX AI stack
TPU Cluster Director overview
Get started
Set up a Google Cloud project
Plan your Cloud TPU resources
Create TPU VMs
Reserve TPUs
About TPU reservations
Request a reservation for up to 90 days (in calendar mode)
Request a future reservation for one year or longer
Share a reservation
Request an All Capacity mode reservation
Consume a reservation
Run JAX on Cloud TPU VM
Run PyTorch on Cloud TPU VM
Train on Cloud TPU slices
Run JAX on Cloud TPU slices
Run PyTorch on Cloud TPU slices
Configure TPUs
Encrypt a TPU VM boot disk with a CMEK
Connect a TPU to a shared VPC network
Connect to a TPU VM without a public IP address
Configure networking and access
Use a cross-project service account
Storage options
Storage options for Cloud TPU
Attach durable block storage to a TPU VM
Connect to Cloud Storage buckets
Mount a Filestore instance on a TPU VM
Training and inference
Train a model using TPU7x
Train a model using v6e
Train a model using v5e
TPU inference
Multislice training
Scale a model on TPUs
Scale ML workloads using Ray
Run TPU applications in a Docker container
Work with image datasets
Convert an image classification dataset for use with Cloud TPU
Download, pre-process and upload the ImageNet dataset
Download, pre-process and upload the COCO dataset
Manage TPUs
Manage TPU resources
Manage queued resources
Request TPU Flex-start VMs
Manage TPU Spot VMs
Manage All Capacity mode TPUs
View the topology and health of All Capacity mode TPUs
Manage All Capacity mode maintenance events
Report and repair faulty hosts in All Capacity mode
Prepare for maintenance events
Schedule TPU collections for inference workloads
Autocheckpoint
View maintenance notifications
Manually start host maintenance
Preemptible TPUs
Optimize performance
Cloud TPU performance guide
Improve your model's performance with bfloat16
TPU7x (Ironwood) performance optimizations
Monitor and troubleshoot TPUs
Troubleshoot TPU VMs
Monitor TPU VMs
Monitor TPU health
Monitor TPU goodput
Dashboards for monitoring and logging
TPU monitoring Library
Monitor with tpu-info CLI
Troubleshoot TensorFlow models
Troubleshoot PyTorch models
Troubleshoot JAX models
Cloud TPU error glossary
Cloud TPU audit logs
ML Diagnostics platform
Overview
Set up GKE
Get started with the SDK
Get started with the CLI
Use ML Diagnostics with MaxText
View machine learning runs
Monitor workloads
Profile TPUs
Profile TPU VMs
Profile Multislice environments
Profile PyTorch XLA workloads
Tutorials
Train ResNet with PyTorch
MaxDiffusion inference on v6e
Notebooks
Notebooks
AI and ML
Application development
Application hosting
Compute
Data analytics and pipelines
Databases
Distributed, hybrid, and multicloud
Industry solutions
Migration
Networking
Observability and monitoring
Security
Storage
Access and resources management
Costs and usage management
