Ray

Ray

Anyscale
+
+

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About

Amazon EC2 Trn2 instances, powered by AWS Trainium2 chips, are purpose-built for high-performance deep learning training of generative AI models, including large language models and diffusion models. They offer up to 50% cost-to-train savings over comparable Amazon EC2 instances. Trn2 instances support up to 16 Trainium2 accelerators, providing up to 3 petaflops of FP16/BF16 compute power and 512 GB of high-bandwidth memory. To facilitate efficient data and model parallelism, Trn2 instances feature NeuronLink, a high-speed, nonblocking interconnect, and support up to 1600 Gbps of second-generation Elastic Fabric Adapter (EFAv2) network bandwidth. They are deployed in EC2 UltraClusters, enabling scaling up to 30,000 Trainium2 chips interconnected with a nonblocking petabit-scale network, delivering 6 exaflops of compute performance. The AWS Neuron SDK integrates natively with popular machine learning frameworks like PyTorch and TensorFlow.

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

Companies in search of a solution to train their large-scale deep learning and generative AI models

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/trn2/

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services
AWS Trainium

AWS Trainium

Amazon Web Services
Keepsake

Keepsake

Replicate

Categories

Categories

Integrations

Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
PyTorch
TensorFlow
AWS Trainium
Amazon EC2 G5 Instances
Amazon EC2 P4 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 UltraClusters
Azure Kubernetes Service (AKS)
Dask
Datadog
Domino Enterprise MLOps Platform
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
MLflow
io.net

Integrations

Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
PyTorch
TensorFlow
AWS Trainium
Amazon EC2 G5 Instances
Amazon EC2 P4 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 UltraClusters
Azure Kubernetes Service (AKS)
Dask
Datadog
Domino Enterprise MLOps Platform
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
MLflow
io.net
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