RayAnyscale
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ScaleCloudScaleMatrix
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Related Products
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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.
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About
Data-intensive AI, IoT and HPC workloads requiring multiple parallel processes have always run best on expensive high-end processors or accelerators, such as Graphic Processing Units (GPU). Moreover, when running compute-intensive workloads on cloud-based solutions, businesses and research organizations have had to accept tradeoffs, many of which were problematic. For example, the age of processors and other hardware in cloud environments is often incompatible with the latest applications or high energy expenditure levels that cause concerns related to environmental values. In other cases, certain aspects of cloud solutions have simply been frustrating to deal with. This has limited flexibility for customized cloud environments to support business needs or trouble finding right-size billing models or support.
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
ML and AI Engineers, Software Developers
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Audience
Hosting platform which enables businesses of any size to control, manage, and customize cloud hardware performance
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Supported
24/7 Live Support
Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Open source. Consumption-based.
Free Version
Supported
Free Trial
Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Company InformationAnyscale
Founded: 2019
United States
ray.io
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Company InformationScaleMatrix
Founded: 2011
United States
www.scalematrix.com/scalecloud
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
Amazon EC2 Trn2 Instances
Supported
Amazon EKS
Supported
Amazon SageMaker
Supported
Amazon Web Services (AWS)
Supported
Anyscale
Supported
Apache Airflow
Supported
Dask
Supported
Databricks
Supported
Feast
Supported
Flyte
Supported
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Integrations
Amazon EC2 Trn2 Instances
Not Supported
Amazon EKS
Not Supported
Amazon SageMaker
Not Supported
Amazon Web Services (AWS)
Not Supported
Anyscale
Not Supported
Apache Airflow
Not Supported
Dask
Not Supported
Databricks
Not Supported
Feast
Not Supported
Flyte
Not Supported
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