Introducing the TensorFlow Research Cloud

The TensorFlow Research Cloud offers researchers the following benefits:

  • Access to Google’s all-new Cloud TPUs that accelerate both training and inference
  • Up to 180 teraflops of floating-point performance per Cloud TPU
  • 64 GB of ultra-high-bandwidth memory per Cloud TPU
  • Familiar TensorFlow programming interfaces

You can sign up here to request to be notified when the TensorFlow Research Cloud application process opens, and you can optionally share more information about your computational needs. We plan to evaluate applications on a rolling basis in search of the most creative and ambitious proposals.

The TensorFlow Research Cloud program is not limited to academia — we recognize that people with a wide range of affiliations, roles, and expertise are making major machine learning research contributions, and we especially encourage those with non-traditional backgrounds to apply. Access will be granted to selected individuals for limited amounts of compute time, and researchers are welcome to apply multiple times with multiple projects.

Since the main goal of the TensorFlow Research Cloud is to benefit the open machine learning research community as a whole, successful applicants will be expected to do the following:

  • Share their TFRC-supported research with the world through peer-reviewed publications, open-source code, blog posts, or other open media
  • Share concrete, constructive feedback with Google to help us improve the TFRC program and the underlying Cloud TPU platform over time
  • Imagine a future in which ML acceleration is abundant and develop new kinds of machine learning models in anticipation of that future

For businesses interested in using Cloud TPUs for proprietary research and development, we will offer a parallel Cloud TPU Alpha program. You can sign up here to learn more about this program. We recommend participating in the Cloud TPU Alpha program if you are interested in any of the following:

  • Accelerating training of proprietary ML models; models that take weeks to train on other hardware can be trained in days or even hours on Cloud TPUs
  • Accelerating batch processing of industrial-scale datasets: images, videos, audio, unstructured text, structured data, etc.
  • Processing live requests in production using larger and more complex ML models than ever before

We hope the TensorFlow Research Cloud will allow as many researchers as possible to explore the frontier of machine learning research and extend it with new discoveries! We encourage you to sign up today to be among the first to know as more information becomes available.

Researchers require enormous computational resources to train the machine learning (ML) models that have delivered recent breakthroughs in medical imaging, neural machine translation, game playing, and many other domains. We believe that significantly larger amounts of computation will make it possible for researchers to invent new types of ML models that will be even more accurate and useful.

To accelerate the pace of open machine-learning research, we are introducing the TensorFlow Research Cloud (TFRC), a cluster of 1,000 Cloud TPUs that will be made available free of charge to support a broad range of computationally-intensive research projects that might not be possible otherwise.

The TensorFlow Research Cloud offers researchers the following benefits:

  • Access to Google’s all-new Cloud TPUs that accelerate both training and inference
  • Up to 180 teraflops of floating-point performance per Cloud TPU
  • 64 GB of ultra-high-bandwidth memory per Cloud TPU
  • Familiar TensorFlow programming interfaces

You can sign up here to request to be notified when the TensorFlow Research Cloud application process opens, and you can optionally share more information about your computational needs. We plan to evaluate applications on a rolling basis in search of the most creative and ambitious proposals.

The TensorFlow Research Cloud program is not limited to academia — we recognize that people with a wide range of affiliations, roles, and expertise are making major machine learning research contributions, and we especially encourage those with non-traditional backgrounds to apply. Access will be granted to selected individuals for limited amounts of compute time, and researchers are welcome to apply multiple times with multiple projects.

Since the main goal of the TensorFlow Research Cloud is to benefit the open machine learning research community as a whole, successful applicants will be expected to do the following:

  • Share their TFRC-supported research with the world through peer-reviewed publications, open-source code, blog posts, or other open media
  • Share concrete, constructive feedback with Google to help us improve the TFRC program and the underlying Cloud TPU platform over time
  • Imagine a future in which ML acceleration is abundant and develop new kinds of machine learning models in anticipation of that future

For businesses interested in using Cloud TPUs for proprietary research and development, we will offer a parallel Cloud TPU Alpha program. You can sign up here to learn more about this program. We recommend participating in the Cloud TPU Alpha program if you are interested in any of the following:

  • Accelerating training of proprietary ML models; models that take weeks to train on other hardware can be trained in days or even hours on Cloud TPUs
  • Accelerating batch processing of industrial-scale datasets: images, videos, audio, unstructured text, structured data, etc.
  • Processing live requests in production using larger and more complex ML models than ever before

We hope the TensorFlow Research Cloud will allow as many researchers as possible to explore the frontier of machine learning research and extend it with new discoveries! We encourage you to sign up today to be among the first to know as more information becomes available.

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