IVAS ZCU104 ML Acceleration Reference Release

Required Tool Version: 2020.1 with Vitis AI 1.2

This repository contains a reference design for the use of the Xilinx IVAS framework in a multi-channel machine learning system. In includes:

  • hw_src with the hardware source files needed to build the Vitis project

  • hls_tests with HLS scripts and test data for validation of individual kernels

  • sw_src contains source code for both individual test applications and the gstreamer pipeline

  • platform contains the platform source

  • vitis_ai_library contains some content overrides for the Vitis AI library

  • vitis_patch contains an SD card packaging patch for Vitis

Note: Vitis Patch Required: This design has a large rootfs, and Vitis 2020.1 has an issue packaging SD card images with ext4 partitions over 2GB. This patch changes the packaging flow to round up the initial rootfs size to the first full multiple of 512MB over the ext4 partition size. To install it:

$ cp ./vitis_patch/mkfsImage.sh ${XILINX_VITIS}/scripts/vitis/util

Build Steps

1. Clone the full repository (including submodules)

$ git clone --recurse-submodules https://github.com/Xilinx/Vitis-In-Depth-Tutorial

Note: Make sure the path where you are cloning this repo is not NFS mounted

2. Build the hardware platform

With Vitis and PetaLinux sourced, change into the platform/dev/zcu104_vcu directory and run make. This will output the platform source to platform/repo/xilinx_zcu104_vcu_202020_1. After building the platform, extract and install the sysroot.

$ cd platform/dev/zcu104_vcu

$ make

$ cd ../../repo/xilinx_zcu104_vcu_202010_1/sysroot

$ ./sdk.sh -d `pwd` -y

3. Build the Vitis design

Source the setup.sh script from your XRT installation area. This platform is built with the 2020.1 release of XRT, version 2.6.655. Version 2.7.766 is also supported. You must use one of these versions; building with different versions of XRT is not supported.

source /opt/xilinx/xrt/setup.sh

One time, and one time only, you must apply the patch in the hw_src directory against the Vitis Vision library.

$ cd hw_src/Vitis_Libraries

$ patch -p1 < ../vision_lib_area_resize_ii_fix.patch

With the patch applied, build the hardware design:

$ cd hw_src

$ make

NOTE: From this point we strongly recommend starting in a ‘fresh’ terminal

4. Source the cross-compilation toolchain

$ cd platform/repo/xilinx_zcu104_vcu_202010_1/sysroot/

$ source ./environment-setup-aarch64-xilinx-linux

5. Build the target software

This is done using a combination of cmake and meson, but requires setup of the cross-compilation environment first. The build process in inludes multiple conceptual submodules using different build systems, so a script has been provided to help automate it and to make the various processes clear.

The script will do the the following things automatically:

  • Add an XRT component to the cross-compilation rootfs for pkfconfig, if it doesn’t already exist

  • Deploy Vitis AI cross-compilation components into the rootfs

  • Configure meson cross-compilation files for the target

  • Build all source references

Note: user to create ml_models folder and keep generated densebox and reid models in it.

Please refer to Vitis AI 1.2 documentation for compiling models

- ml_models/dpu_densebox_640_360.elf
- ml_models/dpu_reid.elf

$ cd sw_src

$ ./go.sh

Preparing the SD Card Image for Boot

1. Burning the image on micro SDcard

Using an SD card flashing tool like dd, Win32DiskImager, or Balena Etcher, burn the image hw_src/sd_card_zcu104/sd_card.img to an SD card and boot the board.

This version uses a non-volatile root file system stored on the SD card. Some post-installation setup is necessary. The following steps are performed on the target post-boot unless otherwise noted.

2. Copy sd_card utilitis

  • Copy sd_card_utils/* to /home/root on the target (we will use these scripts and JSON files in the next step). On the host, run:

$ cd sd_card_utils

$ scp -r * root@<zcu104 board ip>:~

$ scp -r .bashrc root@<zcu104 board ip>:~

3. Copy sw stack

  • Copy update.tar.gz from sw_src/install to the root (/) directory on the board using SSH or similar

$ cd <project_root>/sw_src/install

$ scp update.tar.gz root@<zcu104 board ip>:/

Note: All remaining steps are on the target

4. resize rootfs

Resize the root file system partition to use remaining space on the sd card. You can verify the used disk space before and after with df -h

$ cd ~/scripts

$ ./ext4_auto_resize.sh

5. Install the software libraries and Vitis AI:

$ cd scripts

$ ./update.sh

$ ./install_vai.sh

Note: For the Vitis AI install script to run the board must have a path to the internet (script uses wget to download, so you may be able to set proxy settings). If this is not possible please check the script source and execute the steps manually

  • Copy additional test data (videos, etc) to the same home/root directory (Note that the videos are not part of this repository)

At this point you must reboot the board for all configuration changes to take effect. Do not turn off the power without running shutdown -h now, reboot, or similar

Running the application

$ cd /home/root/scripts

$ ./1ch_crop_reid.sh

  • OPTIONAL: Beginning in Vitis 2020.1, a package feed is available for on-target installation of many different tools. The package manager used is ‘dnf’ which has command line syntax very similar to apt or yum. This requires network connectivity and potentially proxy configuration. To set up this package feed, and to install e.g. the utility vim:

$ cd /home/root/scripts

$ ./package_feed_setup.sh

$ dnf install vim

You may see warnings during DNF package feed setup, these can be ignored.