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Xilinx · Oct 26, 2022 · 411b56c · 411b56c
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 # DPU on PYNQ
 
-This repository holds the PYNQ DPU overlay. Specifically, the Vitis AI DPU 
-is included in the accompanying bitstreams with example training and inference
-notebooks ready to run on PYNQ enabled platforms.
-Steps are also included to rebuild the designs in Vitis and can
-be ported onto PYNQ-enabled Zynq Ultrascale+ boards.
-
-In this repository, we currently support the following boards:
-
-* Ultra96
-* ZCU104
-* KV260
-
-Other Zynq Ultrascale+ boards may be supported with few adjustments.
-This repository supports Vitis AI 1.4.0.
+This repository holds the PYNQ DPU overlay. Specifically, the Vitis AI DPU is included in the accompanying bitstreams with example training and inference notebooks ready to run on PYNQ enabled platforms. Steps are also included to rebuild the designs in Vitis and can be ported onto PYNQ-enabled Zynq Ultrascale+ boards. 
+
+This release of DPU-PYNQ supports PYNQ 3.0 and Vitis AI 2.5.0.
+
+## Board Support
+
+DPU-PYNQ is available for a wide range of boards and devices, some of which may not have official PYNQ images available, however the platforms and overlays can still be used in a variety of custom accelerator applications.
+
+| 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  |   |
+
+DPU overlays for most boards have been built using the B4096 architecture with 1 or 2 cores, compatible with the KV260/ZCU102/ZCU104 models in the Vitis AI Model Zoo. For a selection of smaller boards, like the Ultra96 and ZUBoard-1CG custom arch.json files are provided that will allow you to compile .xmodel files for those boards.
 
 ## Quick Start
 
 ### 1. Install
 
-To install the pynq-dpu on your board, simply run in the jupyter notebooks terminal:
+To install pynq-dpu on your PYNQ-enabled board, in the Jupyter Lab terminal, simply run:
 
 ```shell
 pip3 install pynq-dpu --no-build-isolation
@@ -32,34 +51,41 @@ cd $PYNQ_JUPYTER_NOTEBOOKS
 pynq get-notebooks pynq-dpu -p .
 ```
 
-This will make sure the desired notebooks shows up in your jupyter notebook 
+This will make sure the desired notebooks show up in your jupyter notebook 
 folder.
 
-### 1b. [Optional] Install from ssh
+### 1.b [Optional] Install from ssh/serial
 
-Connect via ssh (e.g., `ssh xilinx@192.168.3.1` on the Ultra96).
+If you are installing the package from an ssh or serial terminal instead of Jupyter Lab (e.g. using the usb network connection on the Ultra96 -- `ssh xilinx@192.168.3.1`).
 
-On Ultra96 and ZCU104, login as `root` (e.g., `sudo su`).
+Make sure you login as `root` (e.g., `sudo su`) and source the pynq profile scripts before installing the pynq_dpu package.
 
 ```shell
-pip3 install pynq-dpu --no-build-isolation
 . /etc/profile.d/xrt_setup.sh
 . /etc/profile.d/pynq_venv.sh
-cd $PYNQ_JUPYTER_NOTEBOOKS
-pynq get-notebooks pynq-dpu -p .
-chown -R xilinx:xilinx pynq-dpu
+pip3 install pynq-dpu --no-build-isolation
 ```
 
 ### 2. Run
 
 You are ready to go! Now in jupyter, you can explore the notebooks 
-in `pynq-dpu` folder.
+in the `pynq-dpu` folder.
+
+## Selftest and Contributing
+
+If you have a board that hasn't been marked as verified in the above table, you can use the new built-in tests to verify if DPU-PYNQ works on your device as intended. To verify that your installation was successful, without opening any notebooks you can run the tests that are part of the pynq_dpu package. Simply run:
+
+```shell
+python3 -m pytest --pyargs pynq_dpu
+```
+
+If the tests are successful please feel free to make a contribution to the above table by opening an pull request and updating the markdown entry for that board.
 
 ## Rebuild DPU Block Design
 
-The DPU IP comes from the [Vitis Ai Github](https://github.com/Xilinx/Vitis-AI/tree/v1.4.0).
+The DPU IP comes from the [Vitis Ai Github](https://github.com/Xilinx/Vitis-AI/tree/v2.5).
 If you want to rebuild the hardware project, you can refer to the
-[instructions for DPU Hardware Design](./boards/README.md).
+[instructions for the DPU Hardware Design](./boards/README.md).
 
 In short, the following files will be generated in `boards/<Board>` folder:
 
@@ -71,8 +97,8 @@ These are the overlay files that can be used by the `pynq_dpu` package.
 
 ## Rebuild DPU Models
 
-[DPU models](https://github.com/Xilinx/Vitis-AI/tree/v1.4) 
-are available on the Vitis AI GitHub repository [model zoo](https://github.com/Xilinx/Vitis-AI/tree/v1.4/models/AI-Model-Zoo),
+[DPU models](https://github.com/Xilinx/Vitis-AI/tree/v2.5) 
+are available on the Vitis AI GitHub repository [model zoo](https://github.com/Xilinx/Vitis-AI/tree/v2.5/model_zoo),
 where you can find a model-list containing quantized models, as well as pre-compiled .xmodel files
 that can be directly loaded into your DPU application.