This page documents production updates to Cloud TPU. You can periodically check this page for announcements about new or updated features, bug fixes, known issues, and deprecated functionality.
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May 7, 2019
Cloud TPU v2 Pod is available in Beta release.
Since TPU resources can scale from a single Cloud TPU to a Cloud TPU Pod, you don't need to choose between a single Cloud TPU and a Cloud TPU Pod. You can request portions of Cloud TPU Pods in slices or sets of cores, so that you purchase only the processing power you need.
Cloud TPU Pod (beta) advantages over a single Cloud TPU v2 device:- Increased training speeds for fast iteration in R&D
- Increased human productivity by providing automatically scalable machine learning (ML) compute
- Ability to train much larger models
Cloud TPU v3 Pod is available in Beta release.
Since TPU resources can scale from a single Cloud TPU to a Cloud TPU Pod, you don't need to choose between a single Cloud TPU and a Cloud TPU Pod. You can request portions of Cloud TPU Pods in slices or sets of cores, so that you purchase only the processing power you need.
Cloud TPU Pod (beta) advantages over a single v3 Cloud TPU device:
- Increased training speeds for fast iteration in R&D
- Increased human productivity by providing automatically scalable machine learning (ML) compute
- Ability to train much larger models
Cloud TPU v3 Pod (beta) advantages over Cloud TPU v2 Pod (beta):
- v2 Pod: 11.5 petaflops and 4 TB on-chip memory (HBM)
- v3 Pod: 100 petaflops and 32 TB HBM, with liquid cooling
March 11, 2019
Cloud TPU now supports TensorFlow version 1.13. Support for Tensorflow versions 1.8 and 1.9 have been removed.
See the current supported TensorFlow versions in the Cloud TPU versioning policy.
January 31, 2019
Cloud TPU v3 is now GA (generally available). Cloud TPU v3 has double the memory of v2. This gives improved performance and enables support for more classes of models, for example deeper ResNets and larger images with RetinaNet. Existing models that run on Cloud TPU v2 will continue to work. Refer to the Cloud TPU versions guide for more information.
November 8, 2018
Cloud TPU now supports TensorFlow version 1.12. This release includes improvements for Keras on Cloud TPUs, performance optimizations throughout the software stack, and improved APIs, error messages, and reliability.
See the current supported TensorFlow versions in the Cloud TPU versioning policy.
November 7, 2018
Cloud TPU v2 Pod is available in Alpha release.
Since TPU resources can scale from a single Cloud TPU to a Cloud TPU Pod, you don't need to choose between a single Cloud TPU and a Cloud TPU Pod. You can request portions of Cloud TPU Pods in slices or sets of cores, so that you purchase only the processing power you need.
Cloud TPU Pod (alpha) advantages:
- Increased training speeds for fast iteration in R&D
- Increased human productivity by providing automatically scalable machine learning (ML) compute
- Ability to train much larger models than on a single ML accelerator
October 10, 2018
Cloud TPU v3 is available in Beta release. You now have a choice between v2 and v3 in your configuration.
- Cloud TPU v3 has double the memory of v2. This gives improved performance and enables support for more classes of models, for example deeper ResNets and larger images with RetinaNet.
- Existing models that run on Cloud TPU v2 will continue to work.
- Refer to the Cloud TPU versions guide for more information.
October 10, 2018
Preemptible TPUs are now GA (generally available). A preemptible TPU is a Cloud TPU node that you can create and run at a much lower price than normal nodes. However, Cloud TPU may terminate (preempt) these nodes if it requires access to the resources for another purpose.
- See how to use a preemptible TPU.
- Review the pricing for preemptible and normal Cloud TPU nodes.
September 27, 2018
Cloud TPU now supports TensorFlow version 1.11. TensorFlow 1.11 introduces experimental support for all of the following on Cloud TPU: Keras, Colab, eager execution, LARS, RNNs, and Mesh TensorFlow. This release also introduces a high-performance Cloud Bigtable integration, new XLA compiler optimizations, other performance optimizations throughout the software stack, and it provides improved APIs, error messages, and reliability.
See the current supported TensorFlow versions in the Cloud TPU versioning policy.
September 7, 2018
Support for TensorFlow version 1.7 ended on September 7, 2018. See the current supported versions in the Cloud TPU versioning policy.
July 24, 2018
We're delighted to announce promotional pricing for Cloud TPU, resulting in significant price reductions. The following table shows the previous pricing and the new pricing available from today:
US
| Previous price per TPU per hour | New price per TPU per hour | |
|---|---|---|
| Cloud TPU | $6.50 USD | $4.50 USD |
| Preemptible TPU | $1.95 USD | $1.35 USD |
Europe
| Previous price per TPU per hour | New price per TPU per hour | |
|---|---|---|
| Cloud TPU | $7.15 USD | $4.95 USD |
| Preemptible TPU | $2.15 USD | $1.485 USD |
Asia Pacific
| Previous price per TPU per hour | New price per TPU per hour | |
|---|---|---|
| Cloud TPU | $7.54 USD | $5.22 USD |
| Preemptible TPU | $2.26 USD | $1.566 USD |
See the pricing guide for details.
July 12, 2018
Cloud TPU is now available in Google Kubernetes Engine as a Beta feature. Run your machine learning workload in a Kubernetes cluster on GCP, and let GKE manage and scale the Cloud TPU resources for you.
- Follow the tutorial to train the Tensorflow ResNet-50 model on Cloud TPU and GKE.
- Refer to the GKE setup guide for quick instructions on running Cloud TPU with GKE.
July 2, 2018
Cloud TPU now supports TensorFlow version 1.9. TensorFlow 1.9 brings increases in Cloud TPU performance as well as improved APIs, error messages, and reliability.
June 27, 2018
Cloud TPU is now GA (generally available). Google's revolutionary TPUs are designed to accelerate machine learning workloads with TensorFlow. Each Cloud TPU provides up to 180 teraflops of performance, providing the computational power to train and run cutting-edge machine learning models.
- Follow the quickstart guide to set up your Cloud TPU.
- Choose a tutorial to run a specific model on your Cloud TPU.
June 18, 2018
Preemptible TPUs are now available in Beta. A preemptible TPU is a Cloud TPU node that you can create and run at a much lower price than normal nodes. However, Cloud TPU may terminate (preempt) these nodes if it requires access to the resources for another purpose.
- See how to use a preemptible TPU.
- Review the pricing for preemptible and normal Cloud TPU nodes.
Cloud TPU is now available in the European (EU) and Asia Pacific (APAC) regions as well as the United States (US). See the the pricing details per region. The following zones are available:
- US
us-central1-bus-central1-cus-central1-f(TFRC program only)
- EU
europe-west4-a
- APAC
asia-east1-c
June 12, 2018
Support for TensorFlow version 1.6 ended on June 12, 2018. See the current supported versions in the Cloud TPU versioning policy.
April 20, 2018
Cloud TPU now supports TensorFlow version 1.8. TensorFlow 1.8 brings increases in Cloud TPU performance as well as improved APIs, error messages, and reliability.
Support for TensorFlow version 1.7 ends on June 20, 2018. See the details in the Cloud TPU versioning policy.
April 2, 2018
Cloud TPU now supports TensorFlow version 1.7. Support for TensorFlow version 1.6 ends on June 2, 2018. See the details in the Cloud TPU versioning policy.
February 12, 2018
Cloud TPU is available in Beta release. Google's revolutionary TPUs are designed to accelerate machine learning workloads with TensorFlow. Each Cloud TPU provides up to 180 teraflops of performance, providing the computational power to train and run cutting-edge machine learning models.
- See how to request TPU quota.
- Follow the quickstart guide to set up your Cloud TPU.
- Choose a tutorial to run a specific model on your Cloud TPU.
