Xilinx/PYNQ

Health v2 · maintenance only

Adoption not part of the score

2339 stars · 861 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PYNQ is an open-source Python framework from AMD/Xilinx for designing embedded systems on Zynq and other adaptive computing platforms (FPGA SoCs). It provides a bootable Linux image with Jupyter Notebooks and a Python package so developers can control programmable logic, hardware overlays, and accelerators without traditional hardware design tools.

Use cases

• accelerate algorithms with FPGA hardware from Python
• build real-time video processing on a Zynq board
• prototype embedded systems with Jupyter notebooks
• teach FPGA and hardware-software co-design to students
• run high frame-rate image processing on programmable logic
• control low-latency IO and signal processing from Python
• deploy hardware overlays on Kria, Alveo, or AWS-F1

When to choose

• you want to use FPGA programmable logic from Python without writing HDL toolflows
• you need rapid prototyping of hardware-accelerated embedded applications
• you are teaching or learning embedded systems and hardware acceleration
• you target supported Zynq, Kria, Alveo, or AWS-F1 boards

When to avoid

• your project targets non-Xilinx/AMD FPGA platforms
• you need bare-metal or RTOS-level control without a Linux image
• you require pure software deployment with no programmable hardware
• you need a lightweight library without board-specific overlays or SD images

Facets

framework · maturity active

embedded sdk machine-learning image-processing video-processing audio-processing developer-tools embedded-systems hardware developer-tools education computer-vision embedded python iot fpga zynq jupyter-notebooks hardware-acceleration programmable-logic xilinx amd overlays soc signal-processing rapid-prototyping automation linux gpu

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markdown · JSON · MCP: product_card(name="Xilinx/PYNQ")