Systolic neural network engine with crossover connection optimization

A method for systolically processing data according to a neural network comprising at least a first layer and a second layer, the method comprising:

• during a first systolic clock cycle, performing a first set of systolic pulses of data through at least first, second, third, and fourth processing units arranged along a first arrangement and at least fifth, sixth, seventh, and eighth processing units arranged along a second arrangement, the first set of systolic pulses including:
• systolically pulsing data from the first processing unit of the first arrangement to the second processing unit of the first arrangement;
• systolically pulsing data from the third processing unit of the first arrangement to the fourth processing unit of the first arrangement;
• systolically pulsing data from the fifth processing unit of the second arrangement to the sixth processing unit of the second arrangement;
• systolically pulsing data from the seventh processing unit of the second arrangement to an eighth processing unit of the second arrangement;
• and
• systolically pulsing data from the second processing unit of the first arrangement to the seventh processing unit of the second arrangement;
• wherein the second processing unit is configured to systolically pulse data to the seventh processing unit along a first interconnect between the first and second arrangements, and wherein the third processing unit is configured to systolically pulse data to the sixth processing unit along a second interconnect between the first and second arrangements.