Accelerating 2d convolutional layer mapping on a dot product architecture

A method for performing a convolution operation, the method comprising:

• storing, by a processor, a convolution kernel in a first storage device of the processor, the convolution kernel having dimensions x by y, wherein x is a number of rows in the convolution kernel and y is a number of columns in the convolution kernel;
• storing, by the processor, in a second storage device of the processor, a first subset of element values of an input feature map having dimensions n by m, wherein n is a number of rows in the input feature map and m is a number of columns in the input feature map;
• performing a first simultaneous multiplication, by the processor, of each value of the first subset of element values of the input feature map with a first element value from among the x*y elements of the convolution kernel;
• for each remaining value of the x*y elements of the convolution kernel, performing, by the processor, a simultaneous multiplication of the remaining value with a corresponding subset of element values of the input feature map;
• for each simultaneous multiplication, storing, by the processor, result of the simultaneous multiplication in an accumulator connected to the processor;
• and
• outputting, by the processor, the values of the accumulator as a first row of an output feature map (OFM).