Ray

Ray

Anyscale
+
+

Related Products

  • Google Cloud Speech-to-Text
    373 Ratings
    Visit Website
  • RunPod
    180 Ratings
    Visit Website
  • ActCAD Software
    401 Ratings
    Visit Website
  • Mentornity
    99 Ratings
    Visit Website
  • ONLYOFFICE Docs
    706 Ratings
    Visit Website
  • Qloo
    23 Ratings
    Visit Website
  • Veryon
    114 Ratings
    Visit Website
  • Syncro
    483 Ratings
    Visit Website
  • Motive
    4,190 Ratings
    Visit Website
  • Chainguard
    43 Ratings
    Visit Website

About

Provision a VM quickly with everything you need to get your deep learning project started on Google Cloud. Deep Learning VM Image makes it easy and fast to instantiate a VM image containing the most popular AI frameworks on a Google Compute Engine instance without worrying about software compatibility. You can launch Compute Engine instances pre-installed with TensorFlow, PyTorch, scikit-learn, and more. You can also easily add Cloud GPU and Cloud TPU support. Deep Learning VM Image supports the most popular and latest machine learning frameworks, like TensorFlow and PyTorch. To accelerate your model training and deployment, Deep Learning VM Images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers and the Intel® Math Kernel Library. Get started immediately with all the required frameworks, libraries, and drivers pre-installed and tested for compatibility. Deep Learning VM Image delivers a seamless notebook experience with integrated support for JupyterLab.

About

Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and professionals seeking a solution to get preconfigured VMs for deep learning applications

Audience

ML and AI Engineers, Software Developers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Google
Founded: 1998
United States
cloud.google.com/deep-learning-vm

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services
Keepsake

Keepsake

Replicate

Categories

Categories

Integrations

Google Cloud Platform
PyTorch
TensorFlow
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon Web Services (AWS)
Anyscale
Azure Kubernetes Service (AKS)
Dask
Feast
Flyte
Google Cloud TPU
Google Compute Engine
Google Kubernetes Engine (GKE)
LanceDB
MLflow
MXNet
Python
Snowflake
io.net

Integrations

Google Cloud Platform
PyTorch
TensorFlow
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon Web Services (AWS)
Anyscale
Azure Kubernetes Service (AKS)
Dask
Feast
Flyte
Google Cloud TPU
Google Compute Engine
Google Kubernetes Engine (GKE)
LanceDB
MLflow
MXNet
Python
Snowflake
io.net
Claim Google Cloud Deep Learning VM Image and update features and information
Claim Google Cloud Deep Learning VM Image and update features and information
Claim Ray and update features and information
Claim Ray and update features and information