HailoRT is a light-weight and production-grade run-time library, which runs on the host processor, and implements a robust user-space run-time library (HailoRT Library) responsible for operating a Hailo device, with intuitive APIs in C/C++ for optimized performance.
HailoRT is comprised of the following main components:
- HailoRT Library.
- HailoRT CLI - command line application used to control the Hailo device, run inference using the device, collect inference statistics and device events, etc.
- HailoRT PCIe Driver - the device driver used to manage the Hailo device, communicate with the device and transfer data to/from the device. The PCIe driver includes the Hailo-8 firmware that runs on the Hailo device, manages the boot and control of the Hailo device.
- pyHailoRT - HailoRT Python API (wraps the run-time library)
- HailoRT GStreamer element (HailoNet).
HailoRT supports Linux and Windows, and can be compiled from sources to be integrated with various x86 and ARM processors.
See hailo.ai developer zone documentation (registration is required for full documentation access).
For HailoRT API examples - see HailoRT examples.
See hailo.ai developer zone - HailoRT changelog (registration required).
Contact information and support is available at hailo.ai.
Hailo-8 is a deep learning processor for edge devices. The Hailo-8 provides groundbraking efficiency for neural network deployment. The Hailo-8 edge AI processor, featuring up to 26 tera-operations per second (TOPS), significantly outperforms all other edge processors. Hailo-8 is available in various form-factors, including the Hailo-8 M.2 Module.
The Hailo-8 AI processor is designed to fit into a multitude of smart machines and devices, for a wide variety of sectors including Automotive, Smart Cities, Industry 4.0, Retail and Smart Homes.
For more information, please visit hailo.ai.