Visualization and Compute GPUs: SolidWorks and Deep Learning Class Types

This article is contributed. See the original author and article here.

With Azure Lab Services, you can easily provide your students with access to high-performing GPUs. 

Azure Lab Services provides several different GPU sizes that you can choose from when you create a lab: 

• Small GPU (Compute) – 6 Cores, 56 GB RAM 
• Small GPU (Visualization) – 6 Cores, 56 GB RAM 
• Medium GPU (Visualization) – 12 Cores, 112 GB RAM

The compute GPU size is intended for compute-intensive applications such as artificial intelligence (AI) and deep learning.  To see an example of a real-world class that uses the Small GPU (Compute) size, we added the Deep Learning in Natural Language Processing class type.  The compute GPU is suitable for this type of class because students use deep learning frameworks and tools that are provided by the Data Science Virtual Machine image to train deep learning models with large sets of data.

The visualization GPU sizes are intended for graphics-intensive applications that involve remote visualization, streaming, gaming, and encoding with frameworks such as OpenGL and DirectX. As an example, we recently added a new class type that shows using the Small GPU (Visualization) size for engineering classes that use SolidWorks.  The visualization GPU is suitable for this type of class because students interact with SolidWorks 3D computer-aided design (CAD) environment for modeling and visualizing solid objects.

For more information, read the article on how to set up a lab with GPU VMs. 

Brought to you by Dr. Ware, Microsoft Office 365 Silver Partner, Charleston SC.