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go-pynq's Introduction

The GO-PYNQ repository is no longer supported.

“GO PYNQ”

  • Contest Sponsored by Xilinx 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.

Application Choices - Using PYNQ

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

Prizes

Guidelines

Stage 1

  • 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.

Required Skills

  • 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)

Schedule

  • 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

Judging Criteria

Support

  • 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

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