Qualcomm AI Engine Direct
The Qualcomm AI Engine Direct SDK (commonly known as the QNN SDK (Qualcomm Neural Network SDK) facilitates the use of various interfaces and artifacts across other processing units such as CPU, NPU, LPAI (Low Power AI), DSP, and GPU, which are collectively known as backends. For more information, refer to Qualcomm documentation.
Embedded Coder® Support Package for Qualcomm® Hexagon® Processors provide Simulink® blocks and MATLAB® System objects to predict the backend response using QNN host and target models, and verify the accuracy and performance before deploying to the backend.
Functions
qnn.getNetworkProperties | Read values for properties defined in QNN model or QNN context binary file (Since R2025b) |
Objects
qnn.CPU | Interface to predict responses of deep learning model for QNN CPU backend (Since R2025b) |
qnn.DSP | Interface to predict responses of deep learning model for QNN DSP backend (Since R2026a) |
qnn.GPU | Interface to predict responses of deep learning model for QNN GPU backend (Since R2026a) |
qnn.HTP | Interface to predict responses of deep learning model for QNN HTP backend (Since R2025b) |
qnn.LPAI | Interface to predict responses of deep learning model for QNN LPAI backend (Since R2025b) |
Blocks
| QNN CPU Predict | Predict responses of QNN model for CPU backend (Since R2025b) |
| QNN DSP Predict | Predict responses of QNN model for DSP backend (Since R2026a) |
| QNN GPU Predict | Predict responses of QNN model for GPU backend (Since R2026a) |
| QNN HTP Predict | Predict responses of QNN model or QNN context binary for HTP (NPU) backend (Since R2025b) |
| QNN LPAI Predict | Predict responses of QNN context binary for LPAI backend (Since R2025b) |
Topics
- Troubleshoot Qualcomm AI Engine Direct Setup for Windows and Linux
Troubleshoot issues in Qualcomm AI Direct Engine setup.
Featured Examples
Deploy Deep Neural Networks to Qualcomm Targets Using Qualcomm AI Engine Direct (QNN)
Learn the workflow for using the Simulink blocks under the QNN Simulink library.
Deploy YOLOX Object Detection and Tracking System on Qualcomm Hexagon NPU
Deploy a YOLOX-based real-time object detection and tracking system on Qualcomm Hexagon NPU using the Qualcomm AI Engine Direct (QNN) SDK.
