Ray

Ray

Anyscale
+
+

Related Products

  • RunPod
    167 Ratings
    Visit Website
  • Vertex AI
    727 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • Kamatera
    151 Ratings
    Visit Website
  • Google Compute Engine
    1,156 Ratings
    Visit Website
  • Amazon Web Services (AWS)
    4,307 Ratings
    Visit Website
  • Qloo
    23 Ratings
    Visit Website
  • Jellyfish
    374 Ratings
    Visit Website
  • AI Docs
    15 Ratings
    Visit Website
  • TelemetryTV
    273 Ratings
    Visit Website

About

Amazon EC2 G4 instances are optimized for machine learning inference and graphics-intensive applications. It offers a choice between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad). G4dn instances combine NVIDIA T4 GPUs with custom Intel Cascade Lake CPUs, providing a balance of compute, memory, and networking resources. These instances are ideal for deploying machine learning models, video transcoding, game streaming, and graphics rendering. G4ad instances, featuring AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, deliver cost-effective solutions for graphics workloads. Both G4dn and G4ad instances support Amazon Elastic Inference, allowing users to attach low-cost GPU-powered inference acceleration to Amazon EC2 and reduce deep learning inference costs. They are available in various sizes to accommodate different performance needs and are integrated with AWS services such as Amazon SageMaker, Amazon ECS, and Amazon EKS.

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 streaming service providers seeking a tool for rendering, encoding, and real-time streaming workloads

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

Amazon
Founded: 1994
United States
aws.amazon.com/ec2/instance-types/g4/

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

Alternatives

Vertex AI

Vertex AI

Google
AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Integrations

Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
AMD Radeon ProRender
Amazon EC2
Amazon Elastic Inference
Anyscale
Azure Kubernetes Service (AKS)
Dask
Feast
Google Cloud Platform
Kubernetes
LanceDB
MLflow
OpenGL
PyTorch
Python
Snowflake
TensorFlow
io.net

Integrations

Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
AMD Radeon ProRender
Amazon EC2
Amazon Elastic Inference
Anyscale
Azure Kubernetes Service (AKS)
Dask
Feast
Google Cloud Platform
Kubernetes
LanceDB
MLflow
OpenGL
PyTorch
Python
Snowflake
TensorFlow
io.net
Claim Amazon EC2 G4 Instances and update features and information
Claim Amazon EC2 G4 Instances and update features and information
Claim Ray and update features and information
Claim Ray and update features and information