DPU-PYNQ v2.5.0 release -- now on 20+ boards

Dear PYNQ users,

DPU-PYNQ now officially supports overlays on 21 boards – which is the most platforms we have seen a design supported on! Additionally, this iteration of DPU-PYNQ supports Vitis AI 2.5.

This release is compatible with:

  • Vitis AI 2.5
  • Vitis / Vivado 2022.1
  • PYNQ v3.0 image

You will notice that some of the overlays have been unverified yet, but since we have the capability of producing a great deal of platforms we decided to share them anyway.

If you are in possession of one of the boards in the unverified overlay list, that has a PYNQ image running on it, you can verify DPU-PYNQ by simply typing in python3 -m pytest --pyargs pynq_dpu after installing DPU-PYNQ on your device. If the tests pass on your board, feel free to let us know that DPU-PYNQ is verified on that board by amending the board support table via a pull request.

Platform DPU Architecture Number of cores Verified
KR260 SOM B4096 1 Yes
KV260 SOM B4096 1 Yes
Pynq-ZU B4096 1 Yes
RFSoC2x2 B4096 2 Yes
RFSoC4x2 B4096 2 Yes
Ultra96v2 B1600 1 Yes
ZCU104 B4096 2 Yes
ZCU111 B4096 2 Yes
ZCU208 B4096 2 Yes
Genesys ZU-5EV B4096 1
T1 Telco RFSoC B4096 2
T1 Telco MPSoc B4096 2
TySOM-3A-ZU19EG B4096 2
TySOM-3-ZU7EV B4096 2
Ultra96v1 B1600 1
UltraZed-EG B4096 1
ZCU102 B4096 2
ZCU106 B4096 2
ZCU1285 B4096 2
ZCU216 B4096 2
ZUBoard-1CG B800 1

Some additional notes:

  1. Most of the supported overlays ship with a B4096 DPU architecture, compatible with the Vitis AI model zoo. This means you can download the .xmodel files from the official Vitis AI repository and use them with DPU-PYNQ overlays.
  2. For other DPU configurations (e.g. Ultra96v1, Ultra96v2 and ZUBoard-1CG), we have provided custom arch.json files and user-friendly scripts for compiling models from the Vitis AI model zoo.
  3. The compile.sh script has been replaced with a python-based alternative called compile.py. It serves the same function, but is slightly more user friendly and expandable.
  4. Thanks to a pull request by one of our community members @haipnh, we now ship with an additional notebook showcasing the yolo_v3 model for object detection.

We always appreciate your engagement and continued contributions. Please use the PYNQ discussion forum to discuss and report any issue.


PYNQ team