Recognition of handwritten MNIST digits on low-memory 2 Kb RAM Arduino board using LogNNet reservoir neural network — mentioned by cpldcpu

Mon, 29 Apr 2024 10:31:45 GMT

On the CH32V003, a load should be two cycles if the code is executed from SRAM, there are additional wait states for load from flash. The V2A does only cache a single 32 bit instruction word, so there is basically no cache. This publication seems to describe more details on the arduino implementation: https://arxiv.org/abs/2105.02953 It appears that the code is even using floats in some implementations, which have to be emulated. So I'd wager that both on algorithmic level (QAT-NN) and implementation level there are some discrepancies that lead to better performance on the CH32V003.

Paper and discussion history. A mention is not an endorsement.

Recognition of handwritten MNIST digits on low-memory 2 Kb RAM Arduino board using LogNNet reservoir neural network · HackerPapers discussions

Recognition of handwritten MNIST digits on low-memory 2 Kb RAM Arduino board using LogNNet reservoir neural network — mentioned by cpldcpu