These instructions will guide you through everything required for building and executing a program on the Ryzen™ AI NPU on Windows. The instructions were tested on a ASUS Vivobook Pro 15.
You will set up a Windows subsystem for Linux (WSL) Ubuntu install, which will be used for building NPU device code. For building the host (x86) code, you will use MS Visual Code Community.
- Rely on WSL Ubuntu 22.04 LTS for Vitis tool install and to build and run our mlir-aie tools
- Rely on MS Visual Studio 17 2022 to natively build the host code (aka test.cpp)
Be sure you have the latest BIOS for your laptop or mini PC, this will ensure the NPU (sometimes referred to as IPU) is enabled in the system. You may need to manually enable the NPU:
Advanced → CPU Configuration → IPU
NOTE: Some manufacturers only provide Windows executables to update the BIOS.
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Turn off SecureBoot (Allows for unsigned drivers to be installed)
BIOS → Security → Secure boot → Disable
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Turn Ac Power Loss to "Always On" (Can be used for PDU reset, turns computer back on after power loss)
BIOS → Advanced → AMD CBS → FCH Common Options → Ac Power Loss Options → Set Ac Power Loss to "Always On"
All steps in WSL Ubuntu terminal.
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Clone https://github.com/Xilinx/mlir-aie.git best under /home/username for speed (yourPathToBuildMLIR-AIE), with submodules:
git clone --recurse-submodules https://github.com/Xilinx/mlir-aie.git
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Prepare WSL2 with Ubuntu 22.04:
- Install packages (after apt-get update):
sudo apt install \ build-essential clang clang-14 lld lld-14 cmake \ libboost-all-dev \ python3-venv python3-pip \ libxrender1 libxtst6 libxi6 \ mingw-w64-tools
- generate locales
apt-get install locales locale-gen en_US.UTF-8
- Install packages (after apt-get update):
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Install Vitis under WSL Ubuntu from Xilinx Downloads and setup a AI Engine license:
- Setup your environment in the following order for aietools and Vitis:
export PATH=$PATH:<Vitis_install_path>/Vitis/2023.2/aietools/bin:<Vitis_install_path>/Vitis/2023.2/bin
- Get local license for AIE Engine tools from https://www.xilinx.com/getlicense providing your machine's MAC address (
ip -brief link show eth0
) - copy license file (Xilinx.lic) to your preferred location (licenseFilePath) and update your setup configuration accordingly, for instance
export XILINXD_LICENSE_FILE=<licenseFilePath>/Xilinx.lic ip link add vmnic0 type dummy ip link set vmnic0 addr <yourMACaddress>
- Setup your environment in the following order for aietools and Vitis:
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Install or Build mlir-aie tools under WSL2:
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Use quick setup script to install from whls:
source utils/quick_setup.sh # NOTE: this will install mlir-aie in my_install/mlir_aie # and llvm in my_install/mlir. Be sure to account for this # using utils/env_setup.sh later on.
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[Optional] Build from source following regular get started instructions https://xilinx.github.io/mlir-aie/Building.html
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After installing the updated Ryzen™ AI driver (see next subsection), use the gendef tool (from the mingw-w64-tools package) to create a .def file with the symbols:
mkdir /mnt/c/Technical/xrtNPUfromDLL; cd /mnt/c/Technical/xrtNPUfromDLL cp /mnt/c/Windows/System32/AMD/xrt_coreutil.dll . gendef xrt_coreutil.dll
All steps in Win11 (powershell where needed).
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Upgrade the NPU driver to version 10.106.8.62 download here, following the instructions on setting up the driver.
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Install Microsoft Visual Studio 17 2022 Community Edition with package for C++ development.
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Install CMake on windows (https://cmake.org/download/)
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Optional (only needed for vision examples): install opencv and add this install to your PATH environmental variable, for instance
C:\Technical\thirdParty\opencv\build\x64\vc16\bin
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Clone https://github.com/Xilinx/XRT for instance under
C:\Technical
andgit checkout 2023.2
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Create a .lib file from the .dll shipping with the driver
- In wsl, generate a .def file (see above)
- Start a x86 Native Tools Command Prompt (installed as part of VS17), go to the folder
C:\Technical\xrtNPUfromDLL
and run command:lib /def:xrt_coreutil.def /machine:x64 /out:xrt_coreutil.lib
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Clone https://github.com/Xilinx/mlir-aie.git for instance under C:\Technical to be used to build designs (yourPathToDesignsWithMLIR-AIE)
To make the compilation toolchain available for use in your WSL terminal, you will need to set some environment variables. We suggest you add the following to a file named setup.sh
, so you can set up your environment easily by running source setup.sh
.
If you used the quick setup script (precompiled mlir-aie binaries), use this setup script.
# NOTE: if you did NOT exit the terminal you can skip this step.
cd <yourPathToDesignsWithMLIR-AIE>
source <yourPathToBuildMLIR-AIE>/ironenv/bin/activate
source yourVitisSetupScript (example shown above)
source <yourPathToBuildMLIR-AIE>/utils/env_setup.sh <yourPathToBuildMLIR-AIE>/my_install/mlir_aie <yourPathToBuildMLIR-AIE>/my_install/mlir
cd <yourPathToDesignsWithMLIR-AIE>
source <yourPathToBuildMLIR-AIE>/sandbox/bin/activate
source yourVitisSetupScript (example shown above)
source <yourPathToBuildMLIR-AIE>/utils/env_setup.sh <yourPathToBuildMLIR-AIE>/install <yourPathToBuildMLIR-AIE>/llvm/install
For your design of interest, for instance from programming_examples, 2 steps are needed: (i) build the AIE desgin in WSL and then (ii) build the host code in powershell.
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Prepare your enviroment with the mlir-aie tools (built during Prerequisites part of this guide). See Set up your environment above.
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Goto the design of interest and run
make
.
Note that your design of interest might need an adapted CMakelists.txt file. Also pay attention to accurately set the paths CMake parameters BOOST_ROOT, XRT_INC_DIR and XRT_LIB_DIR used in the CMakelists.txt, either in the file or as CMake command line parameters.
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Build: Goto the same design of interest folder where the AIE design just got build (see above)
mkdir buildMSVS cd buildMSVS cmake .. -G "Visual Studio 17 2022" cmake --build . --config Release
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Run (program arguments are just an example for add_one design)
cd Release .\<testName>.exe -x ..\..\build\final.xclbin -k MLIR_AIE -i ..\..\build\insts.txt -v 1