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youtube_video_url amazon_s3_presentation_url amazon_s3_video_url categories description image session_attendee_num session_id session_room session_slot session_speakers session_track tag tags title
san19
Python Productivity for Zynq, or PYNQ, has the ability to present programmable logic circuits as hardware libraries called overlays. These overlays are analogous to software libraries. A software engineer can select the overlay that best matches their application. The overlay can be accessed through an application programming interface (API). Using existing community overlays, this course will examine how to experiment with neural networks using PYNQ on Ultra96.
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38
SAN19-313
Sunset V (Session 1)
end_time start_time
2019-09-25 15:25:00
2019-09-25 15:00:00
speaker_bio speaker_company speaker_image speaker_location speaker_name speaker_position speaker_url speaker_username
Tom Curran works on hardware and software for a wide variety of SoC FPGA architecture projects and currently spends most of his time with the Avnet Ultra96 board creating reference designs and training materials for customers as a Sr. Technical Marketing Engineer in the Products & Emerging Technologies team at Avnet. Living in the Boston, MA area, during his career he has worked in various roles on IP development, software drivers, system application software, and embedded Linux development since the mid ‘90s.
Avnet
/assets/images/speakers/san19/tom-curran.jpg
Tom Curran
Sr. Technical Marketing Engineer
tom.curran
AI/Machine Learning
session
96Boards
Industrial
Machine Learning/AI
Open Source Development
Tools
Wednesday
SAN19-313 - Using Python Overlays to Experiment with Neural Networks
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