Systolic neural network processor with feedback control

A method for performing computations of a neural network comprising at least first, second, and third layers, via an array of processing units including at least a first arrangement of first processing units and a last arrangement of second processing units, the method comprising:

• assigning at least a first subset of the first processing units of the first arrangement to the first layer of the neural network;
• assigning at least a subset of the second processing units of the last arrangement to the second layer of the neural network;
• receiving input data for the neural network;
• performing computations of particular nodes of the first layer of the neural network values by using the first subset of the first processing units to process the input data to generate first activation output values;
• performing computations of particular nodes of the second layer of the neural network using the second subset of the second processing units to generate second activation output values;
• sending the second activation output values to a memory;
• re-assigning at least a second subset of the first processing units of the first arrangement to the third layer of the neural network;
• accessing, by the second subset of the first processing units, the second activation output values from the memory;
• and
• performing computations of particular nodes of the third layer of the neural network using the second subset of the first processing units.

A non-transitory computer-readable medium storing computer-executable instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• identifying a neural network for processing by an array of processing units, the neural network including at least first, second, and third layers, and the array including at least a first arrangement of first processing units and a last arrangement of second processing units;
• assigning at least a first subset of the first processing units of the first arrangement to the first layer of the neural network;
• assigning at least a subset of the second processing units of the last arrangement to the second layer of the neural network;
• providing input data for processing by the first subset of the first processing units;
• storing activation output values received from the last arrangement to a memory;
• re-assigning at least a second subset of the first processing units of the first arrangement to the third layer of the neural network;
• and
• providing the activation output values from the memory to the second subset of the first processing units.

A computer-implemented method, comprising:

• determining that a number of layers of a neural network exceeds a number of arrangements of processing units of a systolic processing chip;
• for a first set of forward propagations through a first portion of the neural network, assigning a first arrangement of the number of arrangements to perform computations according to a first layer of the neural network;
• providing an input for the neural network to the first arrangement to initiate the first set of forward propagations;
• storing an output from the systolic processing chip in a memory;
• for a second set of forward propagations through a second portion of the neural network, assigning the first arrangement to perform computations according to a different layer of the neural network;
• and
• providing the output to the first arrangement to initiate the second set of forward propagations.

A device for performing computations of a neural network comprising a number of layers, the device comprising:

• a controller configured to:
• determine that a number of layers of the neural network exceeds a number of arrangements of processing units of a systolic processing chip;
• for a first set of forward propagations through a first portion of the neural network, assign a first arrangement of the number of arrangements to perform computations according to a first layer of the neural network;
• provide an input for the neural network to the first arrangement to initiate the first set of forward propagations;
• store an output from the systolic processing chip in a memory;
• for a second set of forward propagations through a second portion of the neural network, assign the first arrangement to perform computations according to a different layer of the neural network;
• and
• provide the output to the first arrangement to initiate the second set of forward propagations.