Google Cloud Deep Learning VM Image vs. Ray Comparison


Google Cloud Deep Learning VM Image Google	Ray Anyscale	+	+
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About Provision a VM quickly with everything you need to get your deep learning project started on Google Cloud. Deep Learning VM Image makes it easy and fast to instantiate a VM image containing the most popular AI frameworks on a Google Compute Engine instance without worrying about software compatibility. You can launch Compute Engine instances pre-installed with TensorFlow, PyTorch, scikit-learn, and more. You can also easily add Cloud GPU and Cloud TPU support. Deep Learning VM Image supports the most popular and latest machine learning frameworks, like TensorFlow and PyTorch. To accelerate your model training and deployment, Deep Learning VM Images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers and the Intel® Math Kernel Library. Get started immediately with all the required frameworks, libraries, and drivers pre-installed and tested for compatibility. Deep Learning VM Image delivers a seamless notebook experience with integrated support for JupyterLab.	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 Developers and professionals seeking a solution to get preconfigured VMs for deep learning applications	Audience ML and AI Engineers, Software Developers
Support Phone Support Not Supported 24/7 Live Support 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 Not Supported In Person Not Supported	Training Documentation Supported Webinars Supported Live Online Supported In Person Supported
Company Information Google Founded: 1998 United States cloud.google.com/deep-learning-vm	Company Information Anyscale Founded: 2019 United States ray.io
Alternatives AWS Neuron Amazon Web Services	Alternatives Anyscale
AWS Deep Learning AMIs Amazon	Horovod
GPUonCLOUD	Determined AI
Fabric for Deep Learning (FfDL) IBM	Neuralhub
Flower View All	Automaton AI View All
Categories AI Infrastructure Supported Deep Learning Supported	Categories Deep Learning Supported Machine Learning Supported ML Model Deployment Supported

Integrations Google Cloud Platform Supported PyTorch Supported TensorFlow Supported 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 Azure Kubernetes Service (AKS) Not Supported Chainer Supported Dask Not Supported Databricks Not Supported Feast Not Supported Flyte Not Supported Google Compute Engine Supported Kubernetes Not Supported MXNet Supported NVIDIA DRIVE Supported Union Cloud Not Supported Show More Integrations View All 9 Integrations	Integrations Google Cloud Platform Supported PyTorch Supported TensorFlow Supported Amazon EC2 Trn2 Instances Supported Amazon EKS Supported Amazon SageMaker Supported Amazon Web Services (AWS) Supported Anyscale Supported Apache Airflow Supported Azure Kubernetes Service (AKS) Supported Chainer Not Supported Dask Supported Databricks Supported Feast Supported Flyte Supported Google Compute Engine Not Supported Kubernetes Supported MXNet Not Supported NVIDIA DRIVE Not Supported Union Cloud Supported Show More Integrations View All 22 Integrations
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