Windows Platform Support

The DX-M1 / DX-M1M AI accelerator supports Windows 10 / 11 x64. This guide covers driver installation, runtime setup, and application examples to help you get started with NPU inference on Windows.

Prerequisites

• Hardware: DX-M1 or DX-M1M module installed via PCIe / M.2 interface
• OS: Windows 10 or Windows 11 (x64)
• Runtime Library: Microsoft Visual C++ 2015-2022 Redistributable (x64)
• Permissions: Administrator privileges (required for driver installation and service registration)

Driver Installation

The DX-M1 / DX-M1M communicates over PCIe on Windows and requires a companion driver.

First, clone the dx_rt_windows repository. All relative paths in the following steps (such as m1\v3.2.0\...) are relative to the root of this repository:

git clone https://github.com/DEEPX-AI/dx_rt_windows.git
cd dx_rt_windows

1. Navigate to m1/v3.2.0/dxm1drv/
2. Extract dxm1drv.zip to obtain dxm1drv.inf, dxm1drv.sys, and dxm1drv.cat
3. Right-click dxm1drv.inf and select Install
4. After installation, open Device Manager. Under Processing accelerators, you should see DEEPX DEVICE - M1 PCI CONTROLLER

Runtime Installation

Once the driver is installed, set up the runtime daemon.

1. Open Command Prompt (cmd) or PowerShell as Administrator
2. Navigate to the runtime directory (using v3.2.0 as an example):

cd m1\v3.2.0\dx_rt\bin

3. Register and start the DXRT daemon:

dxrtd.exe --install
dxrtd.exe --start

dxrtd.exe is registered as a Windows service and starts automatically on system boot. You can also manage it via services.msc.

Version Selection

Both v3.2.0 and v3.3.1 use the same driver. v3.2.0 provides the full set: driver + runtime + application examples; v3.3.1 includes only the runtime.

Verification

Use dxrt-cli.exe to verify that the NPU device is recognized:

dxrt-cli.exe -s

Successful output should display device information similar to:

Device Information:
  Device ID: 0
  Device Name: DX-M1
  Firmware Version: ...
  Status: Ready

You can also use dxtop.exe for real-time NPU monitoring:

dxtop.exe

Application Examples

Demo Applications (v3.0.2, Recommended)

m1/v3.2.0/dx_app/v3.0.2/ provides prebuilt demo applications covering object detection, face recognition, pose estimation, semantic segmentation, and more.

1. On first use, run m1/v3.2.0/dx_app/setup.bat to download models and sample videos
2. Launch the interactive menu:

cd m1\v3.2.0\dx_app\v3.0.2
run_demo.bat

3. Follow the menu prompts to select a model and run inference

Common models include yolov5_sync, yolov8_sync, scrfd_sync, and efficientnet_sync, each available in synchronous (_sync) and asynchronous (_async) modes.

Python Interface

Install the Python wheel to use the NPU directly from Python:

# Choose the wheel matching your Python version (Python 3.10 ~ 3.14 supported)
pip install m1\v3.2.0\dx_rt\python\dx_engine-1.1.4-cp312-cp312-win_amd64.whl

Python CLI inference example:

python m1\v3.2.0\dx_rt\python\cli\run_model.py -m <model.dxnn> -l 100

Python API example:

from dx_engine import InferenceEngine

engine = InferenceEngine()
engine.load_model("model.dxnn")
engine.run()

Troubleshooting

• DEEPX device not visible in Device Manager: Check the PCIe / M.2 physical connection and ensure the module is properly seated. Try rescanning for hardware changes (devmgmt.msc → Action → Scan for hardware changes).
• dxrt-cli.exe -s fails: Verify that dxrtd.exe is running (check DXRT Daemon service status in services.msc).
• Demo produces no output: Ensure setup.bat has been run to download models and video files. Network access to sdk.deepx.ai is required.
• VC++ errors: Confirm that Microsoft Visual C++ 2015-2022 Redistributable (x64) is installed.