ISAAC: An Analog Convolutional Neural Network Accelerator (Part I) 

The best intro for people outside of the field of system design! (I'm personally more familiar with semiconductor device.) Thank you so much. I understood things very clearly :)

Thanks for the clarified explanation.

Wow this is really cool

If you have a network like this, the currents will not simply be added. In fact you have a complex current divider with multiple voltage sources. The output current is the result of the superposition of all current dividers, which depend on the resistor values and it will get more and more complex by increasing the input vector. Furthermore, the memrisors are changing their values by applying a voltage. How is it possible to get a consistent result?

Do you by any chance have some publicly available code for this architecture?

Why would we need to keep the resolution as opposed to just making a network which is tolerant of error accumulation?

You know how convolutional neural nets can have a dozen hidden layers etc.. Can you have hidden layers, all in analogue before the ADC? Can you have applications which the analogue output is used directly e.g to drive a servo?

Does DA and AD conversion needed between each layer !?

Sir i want expalin for memristor based hardware accelerator for image compression videos details plzzz sir