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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
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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Sunset V (Session 1)
end_time start_time
2019-09-25 15:25:00
2019-09-25 15:00:00
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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.
Tom Curran
Sr. Technical Marketing Engineer
AI/Machine Learning
Machine Learning/AI
Open Source Development
SAN19-313 - Using Python Overlays to Experiment with Neural Networks
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