DeepCube vs. Ray Comparison


DeepCube	Ray Anyscale	+	+
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About DeepCube focuses on the research and development of deep learning technologies that result in improved real-world deployment of AI systems. The company’s numerous patented innovations include methods for faster and more accurate training of deep learning models and drastically improved inference performance. DeepCube’s proprietary framework can be deployed on top of any existing hardware in both datacenters and edge devices, resulting in over 10x speed improvement and memory reduction. DeepCube provides the only technology that allows efficient deployment of deep learning models on intelligent edge devices. After the deep learning training phase, the resulting model typically requires huge amounts of processing and consumes lots of memory. Due to the significant amount of memory and processing requirements, today’s deep learning deployments are limited mostly to the cloud.	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 Professionals interested in a solution to make the training of deep learning models faster	Audience ML and AI Engineers, Software Developers
Support Phone Support 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 Not 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 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 Supported Live Online Supported In Person Supported	Training Documentation Supported Webinars Supported Live Online Supported In Person Supported
Company Information DeepCube Israel www.deepcube.com/technology/	Company Information Anyscale Founded: 2019 United States ray.io
Alternatives NVIDIA DIGITS	Alternatives Anyscale
Fabric for Deep Learning (FfDL) IBM	Horovod
Zebra by Mipsology Mipsology	Determined AI
IBM Watson Machine Learning Accelerator IBM	Neuralhub
Exafunction View All	Automaton AI View All
Categories AI Inference Supported 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 Web Services (AWS) Not Supported Anyscale Not Supported Apache Airflow Not Supported Azure Kubernetes Service (AKS) Not Supported Dask Not Supported Databricks Not Supported Feast Not Supported Flyte Not Supported Google Cloud Platform Not Supported Google Kubernetes Engine (GKE) Not Supported Kubernetes Not Supported LanceDB Not Supported MLflow Not Supported PyTorch Not Supported Python Not Supported Snowflake Not Supported TensorFlow Not Supported io.net Not Supported Show More Integrations	Integrations Amazon EC2 Trn2 Instances Supported Amazon EKS Supported Amazon Web Services (AWS) Supported Anyscale Supported Apache Airflow Supported Azure Kubernetes Service (AKS) Supported Dask Supported Databricks Supported Feast Supported Flyte Supported Google Cloud Platform Supported Google Kubernetes Engine (GKE) Supported Kubernetes Supported LanceDB Supported MLflow Supported PyTorch Supported Python Supported Snowflake Supported TensorFlow Supported io.net Supported Show More Integrations View All 22 Integrations
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