Release Notes

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.

To get the latest product updates delivered to you, add the URL of this page to your feed reader.

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):

  • Faster processing and larger memory:
    • v2 Pod: 11.5 petaflops and 4 TB on-chip memory (HBM)
    • v3 Pod: 100 petaflops and 32 TB HBM, with liquid cooling
  • Can train even larger models
  • 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.

    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.

    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.

    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
    • 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.

    このページは役立ちましたか?評価をお願いいたします。

    フィードバックを送信...