This reference design demonstrates how to use TI Deep Learning (TIDL)/Machine Learning on a Sitara AM57x System-on-Chip (SoC) to bring deep learning inference to an embedded application. This design shows how to run deep learning inference on either C66x DSP cores (available in all AM57x SoCs) and Embedded Vision Engine (EVE) subsystems, which are treated as black boxed deep learning accelerators on the AM5749 SoC.
This reference design is applicable to any application that is looking to bring deep learning/machine learning inference into an embedded application. Customers looking to quickly get started with a deep learning network or to evaluate their own networks performance on an AM57x device will find a step-by-step guide on how to use TIDL available as part of our AM57x Processor SDK.
A fully assembled board has been developed for testing and performance validation only, and is not available for sale.
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Reference design overview and verified performance test data
Detailed schematic diagram for design layout and components
Complete listing of design components, reference designators, and manufacturers/part numbers
Design file that contains information on physical board layer of design PCB
PCB layer plot file used for generating PCB design layout
| Type | Title | Date | ||
|---|---|---|---|---|
| * | Design guide | Deep Learning Inference For Embedded Applications Reference Design | Sep. 11, 2018 | |
| White paper | Bringing deep learning to embedded systems (Rev. A) | Feb. 26, 2019 |
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