Hi, i am a newbie here. Nice to meet u all. Sorry if my English is not good, English is not my first language. I want to ask is Arduino Nano 33 IoT capable to run TensorflowLite library? If it is capable to do so, is there any computing performance difference compared to Arduino Nano 33 BLE?
the Arduino Nano 33 BLE Sense is using a 32-bit ARM Cortex-M4 CPU running at 64 MHz and has 256KB of SRAM and 1MB of CPU Flash memory.
the Arduino Nano 33 IOT, despite the Nano similarity in the name, is using an ARM Cortex-M0 32-bit SAMD21 at 48MHz and has only 32KB of SRAM and 256KB of CPU Flash memory
the difference in capability is significant, probably significant enough that you can't run TensorflowLite
and if you look at the web site, it's not listed as a qualified device
Alright, noted. Thanks for the information. Appreciate your reply.
Welcome to the forum.
As J-M-L said the two devices have two different processors.
For control code the performance per clock cycle is close between the two (~30%).
For computation, the difference of performance is a lot larger. The Cortex-M4 has SIMD instructions that allow multiple data values to be computed at the same time. So, for 8 and 16-bit datatype you can achieve a 2x or 4x performance improvement per clock cycle. For this to work the data needs to be packed.
When it comes to floating point data most Cortex-M4 come with the optional hardware floating point unit (FPU). This allows a 10x performance increase per clock cycle for single-precision floating point operations.
Because you always have some control code and not just the computation the overall performance of the application will be a combination of the above. It’s also depends a bit on the libraries and compilers used.
If you add up the performance per clock cycle and the difference in clock speed for the two boards, there is a significant difference.
and as models can be memory hungry, the extra 224K of SRAM will come handy and might be a problem if you don't have that
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