NETINT AI Overview
This section provides an overview of the NETINT AI NPU (Neural Processing Unit).
NETINT provides a complete end-to-end pipeline to utilize Quadra's 18 TOPS AI inference capability.
NETINT AI Toolkit
The NETINT AI Toolkit provides an Artificial Intelligence development environment for the user to import, quantize, validate, optimize, and export, deep learning models.
To install the NETINT AI Toolkit, please download and untar the installation package called Quadra_AI_V*.tar
To download the latest release, visit our documentation portal
Follow the instruction under the folder documents/
There are also some examples located in the folder examples/
These examples demonstrate the complete workflow, starting with a model import from a third-party framework. The result of the workflow is an optimized network binary graph (NBG), which can be deployed on Quadra’s Neural Processing Units (NPUs).
For more detailed information, please refer to the complete NETINT AI Toolkit User Guide included in the release package.
AI Performance Evaluation
The NETINT AI toolkit also includes a performance evaluation tool called aiperf. The user can use this tool to test the inference performance of Quadra. The tool can also be used to evaluate the accuracy of the network binary graph on Quadra’s hardware.
The aiperf tool uses the API from the libxcoder, which should be installed on the system in advance.
The aiperf tool is contained in the folder aiperf/
For more detailed information, please refer to the complete NETINT AI Toolkit User Guide included in the release package.
AI Python Inference API
For easy integration and fast prototyping, the NETINT AI toolkit provides Python APIs for inferencing with Quarda’s NPU. The Python Inference API follows TensorFlow Lite’s APIs (TFLite).
Some example Python code is located under the folder network_wrapper/
For more detailed information about the Python Inference API, please refer to the included documentation in the AI release package