Apparatus and methods for forward propagation in convolutional neural networks

An apparatus for forward propagation of a convolutional neural network, comprising:

• a master computation circuit configured to
• receive input data, and
• select, in response to an instruction, one or more portions of the input data based on a predetermined convolution window, wherein the instruction is selected from the group consisting of a convolution network sigmoid instruction, a convolution network tanh instruction, a convolution network relu instruction, and a convolution network group instruction,
• wherein the instruction includes a first address of the one or more portions of the input data, a first size of the one or more portions of the input data, a second address of the portion of the convolution kernel, a second size of the portion of the convolution kernel,
• wherein the convolution network sigmoid instruction further includes an indication of a sigmoid function as an activation function,
• wherein the convolution network tanh instruction further includes an indication of a tanh function as the activation function,
• wherein the convolution network relu instruction further includes an indication of a relu function as the activation function, and
• wherein the convolution network group instruction further includes an output address;
• one or more slave computation circuits respectively configured to convolute a portion of a convolution kernel with one of the one or more portions of the input data to generate a slave output value;
• and
• an interconnection circuit configured to combine the one or more slave output values into one or more intermediate result vectors, wherein the master computation circuit is further configured to merge the one or more intermediate result vectors into a merged intermediate vector.