Hardware neural network conversion method, computing device, compiling method and neural network software and hardware collaboration system

A computing device, for converting a neural network application into a hardware neural network fulfilling a hardware constraint condition, comprising a memory and a processor, the memory having computer-executable instructions stored therein, and when executing the computer-executable instructions, the processor executing a method below:

• a neural network connection diagram obtaining step of obtaining a neural network connection diagram corresponding to the neural network application, wherein, the neural network connection diagram is a directed diagram, each node in the diagram represents a layer of neurons, and each edge represents an inter-layer connection relationship;
• a neural network connection diagram splitting step of splitting the neural network connection diagram into neural network basic units, wherein, each neural network basic unit has only ingress nodes and egress nodes without any intermediate layer node, the ingress nodes are in full connection with the egress nodes, all fan-outs of each neuron in the ingress node are within the basic unit, and all fan-ins of each neuron in the egress node are within the basic unit;
• a neural network basic unit conversion step of converting each of the neural network basic units so as to form a network having equivalent functions thereto and formed by connecting basic module virtual entities of neural network hardware, which is referred to as a basic unit hardware network, wherein, one neural network basic unit corresponds to one or more basic module virtual entities of the neural network hardware, and each basic module virtual entity of the neural network hardware fulfills a connectivity constraint condition of a neural network hardware basic module, and is capable of being directly mapped to the neural network hardware basic module;
• and
• a basic unit hardware network connection step of connecting the obtained basic unit hardware networks according to the sequence of splitting so as to create a parameter file for the hardware neural network.

A compiling method for compiling a neural network software application into a hardware neural network, comprising:

• obtaining a neural network software application and a neural network hardware chip configuration situation;
• converting the neural network software application into the hardware neural network, based on the neural network hardware configuration situation, the hardware neural network being formed by connecting basic modules of the neural network hardware chip;
• and
• outputting a parameter file for the hardware neural network, the parameter file describing a connection relationship between the basic modules and a parameter configuration situation of respective basic modules.