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
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.
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Documentation: http://aka.ms/dsvm/ubuntu/docs
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Tutorial: http://aka.ms/linuxwalkthrough
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