embARC Machine Learning Inference (MLI) Workshop
2019-11-19 17:19:33
| Thursday, September 19, 2019 | |
| Santa Clara Marriott
2700 Mission College Blvd, Santa Clara, CA 95054 | |
| Session 1: 11:30 a.m. ¨C 1:30 p.m.
Lunch will be served from 1:30 p.m. ¨C 2:15 p.m. | Session 2: 3:15 p.m. ¨C 5:15 p.m.
Lunch will be served at 1:00 p.m. |
Instructors: Jamie Campbell , Anatoly Savchenkov & Dmitry Zakharov
The embARC Machine Learning Inference (MLI) software library is optimized for low-power IoT applications that utilize convolutional neural networks (CNN) and recurrent neural networks (RNN). During this workshop, participants will get hands-on experience using the MLI library on the 17³Ô¹Ï ARC EM processor, by building an application which uses a CNN to recognize hand-written characters.
Instructors will provide step-by-step instructions and ¡°check points¡± along the way so that everyone can stay on schedule.
Attendees will be able to keep the instructions and the software content will be open-sourced.
Attend this workshop to learn:
? How to implement efficient machine learning ¡°at the edge¡± using 17³Ô¹Ï¡¯ ARC EM processor
? How 17³Ô¹Ï¡¯ optimized open-source Machine Learning Inference libraries target low-power ARC processors
? How to map neural network graphs defined in the TensorFlow framework to low-power ARC processors
? How to create a real-time character-recognition application that runs on ARC EM SDP hardware
? How to work with the ARC MetaWare Development Toolkit to build and debug applications running on the ARC EV processor
*Attendees should have C/C++ programming experience and some basic knowledge of Python.
In this hands-on workshop, you'll:
? Gain an introductory understanding of the embARC MLI Library and basic usage concepts
? Prepare a character-recognition CNN graph using TensorFlow
? Transform and quantize of the graph into an ¡°MLI-ready¡± format
? Integrate the model into an embedded application suitable for execution on the ARC EM-based target
? Execute and test the application
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