I am running computer vision code on a Raspberry Pi on images and considering moving it to a Particle Photon. A Raspberry Pi can do 3.1 GFLOPS (3 billion Floating Operations Per Second). I could not find the performance of the STM32 processor on a Photon.
What is the performance in FLOPS of the particle photon?
Though he platform has no dedicated FPU, you can of course run floating point calculations just fine albeit slower than with FPU. So you “can” but you may not “want to” given your performance expectations (which you did not mention). Knowing a platform’s GFLOPS does little to understand how performance of your calculations will be - your specific algorithm may be more impactful than raw computing power. Lastly, with matrix calculations, memory may be more a limitation depending on how large your matrices are.
If the photon’s speed is not what you need, look for a better algorithm first then for a better platform. This is a ARM cortex m3, next one up would be a cortex m4 but most of those do not have an FPU either (there are a few, if memory serves from NXP). At some point you might be lured into doing hand assembly optimization - i’d stay clear from that as long as you can.