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Description
You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.
Description
High-performance tasks associated with data-heavy AI, IoT, and HPC workloads have traditionally relied on costly, top-tier processors or accelerators like Graphics Processing Units (GPUs) to function optimally. Additionally, organizations utilizing cloud-based platforms for demanding computational tasks frequently encounter trade-offs that can be less than ideal. For instance, the outdated nature of processors and hardware in cloud infrastructures often fails to align with the latest software applications, while also raising concerns over excessive energy consumption and environmental implications. Furthermore, users often find certain features of cloud services to be cumbersome and challenging, which hampers their ability to create tailored cloud solutions that meet specific business requirements. This difficulty in achieving a perfect balance can lead to complications in identifying appropriate billing structures and obtaining adequate support for their unique needs. Ultimately, these issues highlight the pressing need for more adaptable and efficient cloud solutions in today's technology landscape.
API Access
Has API
API Access
Has API
Integrations
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
Anyscale
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks
Feast
Integrations
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
Anyscale
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks
Feast
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Anyscale
Founded
2019
Country
United States
Website
ray.io
Vendor Details
Company Name
ScaleMatrix
Founded
2011
Country
United States
Website
www.scalematrix.com/scalecloud
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Cloud Management
Access Control
Billing & Provisioning
Capacity Analytics
Cost Management
Demand Monitoring
Multi-Cloud Management
Performance Analytics
SLA Management
Supply Monitoring
Workflow Approval