The GO-PYNQ repository is no longer supported.

“GO PYNQ”

Moto

To build an AI, Machine Learning, Internet of Things targeting application on Ultra96 or PYNQ-Z2 kit using open-source PYNQ framework.

Depends on your creativity, e.g. IoT, Video Processing, Any compute heavy workload being accelerated.

Submission of Abstract with detailed description of the application including proposed technical approach to develop it. Description must include potential kit selection (either Ultra96 or Pynq-Z2 Kit) with a short justification. Top abstracts will qualify to Stage 2 and receive Ultra96/Pynq-Z2 Kits for actual implementation.
Stage 2
Demo Video Submission of 2 minute of final application , source files submissions along with a final report. Winners will be selected based on actual implementation and application complexity.

Creative Problem Identification
Python (working knowledge)
Domain Knowledge (of the problem space identified)
Hardware Knowledge (to be able to understand hardware resources available on PYNQ)

Last date for registration - 5th November
Last date for Abstract submission - 5th November (Hence it is advised to start working as soon as you register)
Results and Shortlisting of teams for Stage 2 - 15th November
Last date for submission of Demo Video Report - 20th December
Final Results - 3rd January

PYNQ being open sourced project of Xilinx, much of the information is available online: http://www.pynq.io/
Checkout the Presentations and Quickstart sections in this repo
One pre-determined slot one hour per week, given by Xilinx Employee for support/brainstorming