Microsoft’s Batch AI Service – Train & test machine learning models, on pools of GPU machines.




Microsoft Batch AI

Microsoft’s Batch AI Service is a new service that helps you train and test machine learning models, including deep learning models, on pools of GPU machines. It simplifies the process of creating a cluster of machines and training on it using many popular deep learning frameworks like TensorFlow, Microsoft Cognitive Toolkit, and others.

The Ubuntu Data Science Virtual Machine is supported as a native VM image in Batch AI. The Ubuntu DSVM comes with many deep learning frameworks, GPU drivers, CUDA, and cuDNN pre-installed, so it is easy to get started with a deep learning project. see details below.

Data scientists can develop an initial version of a model on a single DSVM, using a smaller dataset, then easily scale out across many DSVMs and larger datasets in Batch AI when ready. Using the same DSVM image in Batch AI minimizes the setup time required for your cluster’s VMs and reduces incompatibilities between Batch AI and your development environment.

Microsoft Batch AI handles the details of setting up your cluster, can automatically scale up and down based on demand, and supports low-priority VMs for additional cost savings. Microsoft Batch AI also lets you run parameter sweeps in parallel. Managing data is an integral part of deep learning, and Batch AI includes native support for file shares and NFS servers.

Microsoft Batch AI Resources

Read more at Batch AI Overview and see their recipes for examples with TensorFlow, Microsoft Cognitive Toolkit, Keras, Chainer, and others.

Azure Low Priority VM https://docs.microsoft.com/en-us/azure/batch/batch-low-pri-vms

Microsoft Batch AI Docs https://docs.microsoft.com/azure/batch-ai

Learn about Azure Batch AI

Get started using Azure CLI

Get started using Python

Microsoft Data Science Virtual Machine



DSVM Overview: http://aka.ms/dsvm/overview

DSVM Reference: https://docs.microsoft.com/azure/machine-learning/data-science-virtual-machine/dsvm-tools-overview

Deep Learning: https://docs.microsoft.com/azure/machine-learning/data-science-virtual-machine/use-deep-learning-dsvm

Support & Queries see Community Forum: http://aka.ms/dsvm/forum

Ubuntu Edition

The Ubuntu DSVM is supported as a native VM image in Batch AI. The Ubuntu DSVM comes with many deep learning frameworks, GPU drivers, CUDA, and cuDNN pre-installed, so it is easy to get started with a deep learning project. Data scientists can develop an initial version of a model on a single DSVM, using a smaller dataset, then easily scale out across many DSVMs and larger datasets in Batch AI when ready. Using the same DVM image in Batch AI minimizes the setup time required for your cluster’s VMs and reduces incompatibilities between Batch AI and your development environment. Batch AI handles the details of setting up your cluster, can automatically scale up and down based on demand, and supports low-priority VMs for additional cost savings. Read more at Batch AI Overview and see their recipes for examples with TensorFlow, Microsoft Cognitive Toolkit, Keras, Chainer, and others.

Comments (0)

Skip to main content