Deeplearning4j vs. Ray Comparison


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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 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	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
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 Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not Supported Free Trial Not Supported	Pricing Free Open source. Consumption-based. Free Version Supported Free Trial Supported
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 Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Supported Live Online Supported In Person Supported
Company Information Deeplearning4j Founded: 2019 Japan deeplearning4j.org	Company Information Anyscale Founded: 2019 United States ray.io
Alternatives MXNet The Apache Software Foundation	Alternatives Anyscale
Fabric for Deep Learning (FfDL) IBM	Horovod
Apache Mahout Apache Software Foundation	Determined AI
MLlib Apache Software Foundation	Neuralhub
Apache Spark Apache Software Foundation View All	Automaton AI View All
Categories Deep Learning Supported Neural Network Supported	Categories Deep Learning Supported Machine Learning Supported ML Model Deployment Supported

Integrations Amazon EC2 Trn2 Instances Not Supported Amazon EKS Not Supported Amazon SageMaker Not Supported Amazon Web Services (AWS) Not Supported Apache Airflow Not Supported Apache Spark Supported Azure Kubernetes Service (AKS) Not Supported Dask Not Supported Databricks Not Supported Feast Not Supported Flyte Not Supported Google Cloud Platform Not Supported Hadoop Supported Kubernetes Not Supported LanceDB Not Supported Python Not Supported Snowflake Not Supported TensorFlow Not Supported Union Cloud Not Supported io.net Not Supported Show More Integrations View All 2 Integrations	Integrations Amazon EC2 Trn2 Instances Supported Amazon EKS Supported Amazon SageMaker Supported Amazon Web Services (AWS) Supported Apache Airflow Supported Apache Spark Not Supported Azure Kubernetes Service (AKS) Supported Dask Supported Databricks Supported Feast Supported Flyte Supported Google Cloud Platform Supported Hadoop Not Supported Kubernetes Supported LanceDB Supported Python Supported Snowflake Supported TensorFlow Supported Union Cloud Supported io.net Supported Show More Integrations View All 22 Integrations
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