Ray

Ray

Anyscale
+
+

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About

DL4J takes advantage of the latest distributed computing frameworks including Apache Spark and Hadoop to accelerate training. On multi-GPUs, it is equal to Caffe in performance. The libraries are completely open-source, Apache 2.0, and maintained by the developer community and Konduit team. Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API. Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs. There are a lot of parameters to adjust when you're training a deep-learning network. We've done our best to explain them, so that Deeplearning4j can serve as a DIY tool for Java, Scala, Clojure, and Kotlin programmers.

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

Researchers, developers and professionals requiring an open-source, distributed, deep learning library for the JVM

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

Deeplearning4j
Founded: 2019
Japan
deeplearning4j.org

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

MXNet

MXNet

The Apache Software Foundation

Alternatives

Vertex AI

Vertex AI

Google
AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Integrations

Amazon EC2 Trn2 Instances
Amazon EKS
Amazon Web Services (AWS)
Anyscale
Apache Airflow
Apache Spark
Azure Kubernetes Service (AKS)
Dask
Feast
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
Hadoop
Kubernetes
MLflow
PyTorch
Snowflake
TensorFlow
Union Cloud
io.net

Integrations

Amazon EC2 Trn2 Instances
Amazon EKS
Amazon Web Services (AWS)
Anyscale
Apache Airflow
Apache Spark
Azure Kubernetes Service (AKS)
Dask
Feast
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
Hadoop
Kubernetes
MLflow
PyTorch
Snowflake
TensorFlow
Union Cloud
io.net
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