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The AzureCAT blog has moved! Find this blog post over on our new blog at the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/AzureCAT/NEW-REFERENCE-ARCHITECTURE-Distributed-training-of-deep-learning/ba-p/333652
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Our sixth AI reference architecture (on the Azure Architecture Center) is authored by AzureCAT Mathew Salvaris, edited by Nanette Ray, and published by Mike Wasson.
Reference architectures provide a consistent approach and best practices for a given solution. Each architecture includes recommended practices, along with considerations for scalability, availability, manageability, security, and more. This architecture includes a deployable solution as well. The full array of reference architectures is available on the Azure Architecture Center.
This reference architecture shows how to conduct distributed training of deep learning models across clusters of GPU-enabled virtual machines (VMs). The scenario is image classification, but the solution can be generalized for other deep-learning scenarios, such as segmentation and object detection.
This architecture consists of the following components:
Topics covered include:
Head over to the Azure Architecture Center to learn more about the Distributed training of deep learning models on Azure reference architecture.
Additional related AI reference architectures:
Find all our reference architectures here.
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