The e-AI is solution to enable the Artificial Intelligence(hereafter AI) technology to embedded systems.
AI consists of “Training” and “Inference”.
Renesas‘ e-AI solution enables the use of AI by running only “inference” on MCUs and MPUs.
Also refer the “What is Renesas’ e-AI Solution?”
Advantage of e-AI
The biggest advantage of e-AI is “real-time processing”
e-AI can judge or response without delay of network, therefore it can get the result of inference faster than cloud case.
e-AI can be used where continuous input data is judged one after another with AI by using this real-time performance.
Renesas will contribute to the realization of an environmentally friendly smart society that supports safer and healthier lifestyles through innovations from endpoint intelligence.
Correspondence between AI application examples and MCUs/MPUs
There are many AI application examples, and the requirements of memory size / performance are different. Refer to following figure for choosing which MCU/MPU is good for your AI application.
e-AI development environment
Renesas provides the e-AI development environment to realize AI implementation easier for MCU or AI accelerator.
When user inputs the trained AI model into this tool, then the tool converts to a program that runs on the MCU or AI accelerator without any additional operations.
Downloads of e-AI development environment
Download e-AI development environment from these pages.
This tool supports many kinds of Renesas’ microcomputers. The tool can convert from trained model of “PyTorch”, “Keras”, “Tensorflow”, or 8-bit quantized model of “TensorFlow Lite” and import it easily to e2 studio that is Renesas' integrated development environment. These kind of Renesas products are suitable to be used for relatively small-scale AI for endpoints.
Released e-AI Translator V2.2.0. (Mar. 2022.)
Addition of new function “CMSIS_INT8” for high-speed inference operation of ”TensorFlow Lite” 8-bit quantized model. (Support RA, RX families)
Released CMSIS for RX library V1.0.0, additionally. (Mar. 2022.)
This library is required to use the new function “CMSIS_INT8” for RX family
This tool supports RZ/V series equipped with the AI accelerator "DRP-AI".
This tool can convert from ONNX format that trained by framework such as “PyTorch” to DRP-AI object code.
These Renesas products are suitable to be used for relatively mid-scale AI for endpoints or edge.
e-AI supported products
Each development environments are supported following products
Supported Products by e-AI Translator
|Supported Products by e-AI Translator|
|RA Family||ecosystem partner|
|RZ/A Series||ecosystem partner|
|RE Family||ecosystem partner|
|RL78 Family||ecosystem partner|
|RX Family||ecosystem partner|
|Renesas Synergy™ Platform||ecosystem partner|
Supported Products by DRP-AI Translator
|Supported Products by DRP-AI Translator|
|RZ/V series||ecosystem partner|
Our experiment by Renesas Naka Fab
A demonstration experiment on equipment abnormality detection and predictive maintenance by e-AI was conducted (2015) at the semiconductor front-end factory -"Renesas Naka factory (Renesas Semiconductor Manufacturing Co., Ltd.)"- in Hitachinaka City, Ibaraki Prefecture. New added value, such as abnormality detection and predictive maintenance, can be realized without making major remodeling to existing facilities, while utilizing the existing facilities. In addition, e-AI has greatly improved detection precision with regard to facility abnormalities that previously could only be properly judged by a skilled technician or operator. We have received inquiries from more than 40 customers from Japan and overseas, and started discussions with more than 10 AI-related partners for concretization of business. This example convinced customers that e-AI could contribute to their business and could solve social problems. At the Naka factory, preparations are now under-way for practical use of e-AI for abnormality detection and predictive maintenance.
Plug-ins for e² studio for connecting AI and embedded systems are available.