Speed up your Portenta, but use more memory

#1

I just tested a weird compiler flag that is set on the Portenta. (in the variants/PORTENTA_H7_M7/cflags.txt file, where you switch the default setting on line 14 from -Os to -O3) Read about it here

So my vision ML program can just fit on the regular M7 core, with this change it uses more RAM and I needed to switch to the 1.5M M7 and 0.5M M4 core setting but my classification time went from 121 ms to 101 ms a 20 ms improvement

So about a 20% speed improvement for a slightly bigger program.

Here is my data

using 0s flag using the 1.0 M7 and 1.0 M5 core split

Sketch uses 776368 bytes (98%) of program storage space. Maximum is 786432 bytes.
Global variables use 89808 bytes (17%) of dynamic memory, leaving 433816 bytes for local variables. Maximum is 523624 bytes.
dfu-util 0.10-dev


run_classifier returned: 0
Predictions (DSP: 1 ms., Classification: 121 ms., Anomaly: 0 ms.): 
[0.94531, 0.05078, 0.00391, 0.00000]




using O3 flag   using 1.5 M7 and  0.5 M4 core split

Sketch uses 806184 bytes (55%) of program storage space. Maximum is 1441792 bytes.
Global variables use 89808 bytes (17%) of dynamic memory, leaving 433816 bytes for local variables. Maximum is 523624 bytes.
dfu-util 0.10-dev



run_classifier returned: 0
Predictions (DSP: 1 ms., Classification: 101 ms., Anomaly: 0 ms.): 
[0.99609, 0.00000, 0.00000, 0.00000]
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#2

Hello @Rocksetta,

FYI, we just officially released the Arduino Portenta H7 with full support: https://www.edgeimpulse.com/blog/announcing-official-support-for-the-arduino-portenta-h7
I thought you might be interested. Feel free to ping me for any question.

Regards,

Louis

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#3

@louis. I have tested the Camera Arduino code and it works great. Today testing the Microphone. Well done all Edge Impulse people who worked on this. It is such a big deal to combine the ease of Arduino with the power of both Edge Impulse and the amazing Portenta with either the LoRa or Ethernet Vision Shields.

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