No
Yes
View More
View Less
Working...
Close
OK
Cancel
Confirm
System Message
Delete
Schedule
An unknown error has occurred and your request could not be completed. Please contact support.
Scheduled
Wait Listed
Personal Calendar
Speaking
Conference Event
Meeting
Interest
Schedule TBD
Conflict Found
This session is already scheduled at another time. Would you like to...
Loading...
Please enter a maximum of {0} characters.
Please enter a maximum of {0} words.
must be 50 characters or less.
must be 40 characters or less.
Session Summary
We were unable to load the map image.
This has not yet been assigned to a map.
Search Catalog
Reply
Replies ()
Search
New Post
Microblog
Microblog Thread
Post Reply
Post
Your session timed out.
This web page is not optimized for viewing on a mobile device. Visit this site in a desktop browser to access the full set of features.
2017 GTC San Jose

S7397 - GPU-Accelerated Deep Learning Framework for Cyber-Enabled Manufacturing

Session Speakers
Session Description

We'll present a GPU-accelerated deep-learning framework for cyber-manufacturing, which enables real-time feedback to designers regarding the manufacturability of a computer-aided design model. We'll talk about a 3D-convolutional neural network-based approach for learning the manufacturability of a mechanical component. The 3D-CNN can recognize the features in a CAD model and classify it to be manufacturable or non-manufacturable with a greater accuracy than traditional rule-based methods. We'll discuss a novel GPU-accelerated voxelization algorithm used to discretize the CAD model and prepare it for deep learning. We'll briefly outline the challenges in training a 3D-CNN using complex CAD models on a GPU (NVIDIA TITAN X) with limited memory. Finally, we'll touch upon different methods to extend the framework to other manufacturing processes, such as additive manufacturing and milling.


Additional Session Information
Intermediate
Talk
Computational Fluid Dynamics Computer Aided Engineering Deep Learning and AI Intelligent Machines and IoT Manufacturing Industries
Higher Education / Research Manufacturing
25 minutes
Session Schedule