Reduced power consumption analog or hybrid mac neural network

A method of improving implementation of an artificial intelligence (AI) neural network (NN) model, the method comprising:

• performing multiply and accumulate (MAC) operations on inputs and weights provided to a MAC circuit;
• generating an analog output from the MAC operations;
• partially converting, by an analog to digital converter (ADC), the analog output to a digital output;
• determining that a sign of the digital output based on the partial conversion;
• is a first sign or a second sign, wherein the second sign is different from the first sign;
• completing conversion of the analog output to the digital output by the ADC responsive to at least the sign being the first sign;
• and
• reducing power consumption of the MAC circuit by stopping conversion of the analog output to the digital output by the ADC based at least on an indication of a first type of activation function applied to the digital output and responsive to at least the sign being the second sign.

A system, comprising:

• one or more memory devices that store a deep neural network (DNN) topology and a neural processing unit (NPU) comprising:
• a multiply and accumulate (MAC) circuit comprising:
• a plurality of MAC processing elements (PEs) configured to generate an analog output from multiply and accumulation operations on inputs and weights;
• an analog to digital converter (ADC) configured to convert the analog output to a digital output;
• and
• an ADC controller configured to selectively stop the ADC before completely converting the analog output to the digital output based at least on an indication of a type of activation function applied to the digital output and a sign of the digital output, thereby reducing power consumption of the MAC circuit.