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What is Ray?

You can start developing on your laptop and then effortlessly scale your Python code across numerous GPUs in the cloud. Ray transforms conventional Python concepts into a distributed framework, allowing for the straightforward parallelization of serial applications with minimal code modifications. With a robust ecosystem of distributed libraries, you can efficiently manage compute-intensive machine learning tasks, including model serving, deep learning, and hyperparameter optimization. Scaling existing workloads is straightforward, as demonstrated by how Pytorch can be easily integrated with Ray. Utilizing Ray Tune and Ray Serve, which are built-in Ray libraries, simplifies the process of scaling even the most intricate machine learning tasks, such as hyperparameter tuning, training deep learning models, and implementing reinforcement learning. You can initiate distributed hyperparameter tuning with just ten lines of code, making it accessible even for newcomers. While creating distributed applications can be challenging, Ray excels in the realm of distributed execution, providing the tools and support necessary to streamline this complex process. Thus, developers can focus more on innovation and less on infrastructure.

What is AWS Neuron?

The system facilitates high-performance training on Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances, which utilize AWS Trainium technology. For model deployment, it provides efficient and low-latency inference on Amazon EC2 Inf1 instances that leverage AWS Inferentia, as well as Inf2 instances which are based on AWS Inferentia2. Through the Neuron software development kit, users can effectively use well-known machine learning frameworks such as TensorFlow and PyTorch, which allows them to optimally train and deploy their machine learning models on EC2 instances without the need for extensive code alterations or reliance on specific vendor solutions. The AWS Neuron SDK, tailored for both Inferentia and Trainium accelerators, integrates seamlessly with PyTorch and TensorFlow, enabling users to preserve their existing workflows with minimal changes. Moreover, for collaborative model training, the Neuron SDK is compatible with libraries like Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP), which boosts its adaptability and efficiency across various machine learning projects. This extensive support framework simplifies the management of machine learning tasks for developers, allowing for a more streamlined and productive development process overall.

Media

Media

Integrations Supported

Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
Apache Airflow
Dask
Feast
Google Cloud Platform
LanceDB
PyTorch
Python
Snowflake

Integrations Supported

Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
AWS Deep Learning AMIs
AWS Deep Learning Containers
AWS Trainium
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon Elastic Container Service (Amazon ECS)

API Availability

Has API

API Availability

Pricing Information

Free
Open source. Consumption-based.
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Anyscale

Date Founded

2019

Company Location

United States

Company Website

ray.io

Company Facts

Organization Name

Amazon Web Services

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/machine-learning/neuron/

Categories and Features

Deep Learning

Not specified

Machine Learning

Not specified

ML Model Deployment

Not specified

Categories and Features

AI Inference

Not specified

AI Infrastructure

Not specified

AI/ML Model Training

Not specified

Deep Learning

Not specified

Machine Learning

Not specified

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