Methods for processing data in an efficient convolutional engine with partitioned columns of convolver units

A method for processing input data with a first input channel and a second input channel, the method comprising:

• processing, by a first plurality of convolver units belonging to a first plurality of columns of a convolutional engine, the first input channel, the processing of the first input channel comprising computing a first plurality of dot products based on the first input channel and a first plurality of filter weights, and providing the first plurality of dot products to accumulators of the first plurality of convolver units;
• processing, by a second plurality of convolver units belonging to a second plurality of columns of the convolutional engine disjoint from the first plurality of columns, the first input channel, the processing of the first input channel comprising computing a second plurality of dot products based on the first input channel and a second plurality of filter weights, and providing the second plurality of dot products to accumulators of the second plurality of convolver units;
• processing, by the first plurality of convolver units, the second input channel, the processing of the second input channel comprising computing a third plurality of dot products based on the second input channel and a third plurality of filter weights, and summing the first plurality of dot products and the third plurality of dot products with the accumulators of the first plurality of convolver units;
• and
• processing, by the second plurality of convolver units, the second input channel, the processing of the second input channel comprising computing a fourth plurality of dot products based on the second input channel and a fourth plurality of filter weights, and summing the second plurality of dot products and the fourth plurality of dot products with the accumulators of the second plurality of convolver units.