Method of operating neural networks, corresponding network, apparatus and computer program product

A neural network, comprising:

• one or more inputs, which, in operation, receive input data;
• one or more outputs, which, in operation, output one or more output signals;
• and
• a plurality of network layers coupled between the one or more inputs and the one or more outputs, and which, in operation, perform classification operations, the performing including generating the one or more output signals based on the input data, the plurality of network layers including a set of operating circuits, which, in operation:
• scale respective sets of data using input scaling factors;
• convert scaled sets of data to a Residual Number System (RNS) domain from one or more other domains, wherein input scaling factors applied to a set of data determine a range of the RNS domain;
• perform arithmetic operations in the RNS domain on the converted data;
• convert respective results of the arithmetic operations from the RNS domain to the one or more other domains;
• and
• scale the converted results using output scaling factors complementary to the input scaling factors.

A system, comprising:

• circuitry, which, in operation, generates source data;
• and
• a neural network coupled to the circuitry, wherein the neural network, in operation, performs classification operations, the performing classification operations including generating one or more output signals based on the source data and including a set of operating circuits, wherein the operating circuits, in operation:
• scale respective sets of data using input scaling factors;
• convert scaled sets of data to a Residual Number System (RNS) domain from one or more other domains, wherein input scaling factors applied to a set of data determine a range of the RNS domain;
• perform arithmetic operations in the RNS domain on the converted data;
• and
• convert respective results of the arithmetic operations from the RNS domain to the one or more other domains;
• and
• scale the converted results using output scaling factors complementary to the input scaling factors.

A non-transitory computer-readable medium whose contents configure a set of operating circuits of a neural network having a plurality of layers to perform a method, the method comprising:

• scaling input data to the set of operating circuits using input scaling factors;
• converting scaled input data to the set of operating circuits of the neural network to a Residual Number System (RNS) domain from one or more other domains, the input scaling factors determining a range of represented values in the RNS domain;
• performing arithmetic operations in the set of operating circuits in the RNS domain on the converted data;
• converting output results of the arithmetic operations of the set of operating circuits from the RNS domain to the one or more other domains;
• scaling the converted output results in the one or more other domains using output scaling factors complementary to the input scaling factors, generating scaled output results;
• and
• performing a classification operation based on the scaled output results.