ESP32 S3 AI Acceleration Support

[Rumidom]

Acording to espressif ESP32-S3 has AI Acceleration Support

AI Acceleration Support
ESP32-S3 has additional support for vector instructions in the MCU, which provides acceleration for neural network computing and signal processing workloads. Developers can take advantage of these vector instructions through ESP-DSP and ESP-NN libraries to optimize their applications. ESP-WHO and ESP-Skainet SDKs will also support this acceleration.

is there any way of accessing those instructions via micropython? so far I only found resources on how to access it using their oficial library would be really cool to be able to inference models on it especially using python

[Rumidom]

it seems like the esp-dsp library implements vector operations in c not sure how hard it would be to port those over to micropython, I think I'll try doing that and maybe create a simple micrograd/tinygrad library on top of it. But just the inference part, it would be awesome to be able to run tinygrad models on a esp32

[jonnor]

The easiest would be to create some MicroPython C modules that exposes APIs for the relevant functionality. For inspiration, see how emlearn-micropython works - it implements classical ML models in C and MicroPython APIs.

[Rumidom]

according to this 10297 you cant access esp-idf in native code modules, so I guess the esp-dsp library wouldn't work ? is there a way to write esp32 assembly code as a .mpy module for micropython?

[jonnor]

That limitation is only for dynamically loaded C modules (.mpy files). A user module which is built together with the firmware does not have that limitation.

[Rumidom]

I found this example on how to use the ESP32 S3 SIMD instructions on arduino

[NowLoadY]

Is AI inference possible on the ESP32-S3 using MicroPython? Yes, that's what I'm expecting.😀

[NowLoadY]

with acceleration) haha