Amazon Technologies, Inc.

Perceive Corporation

Won Rhee

Steven L Teig

Kenneth Duong

Jung Ko

Some embodiments provide a method that receives a specification of a neural network for execution by an integrated circuit. The integrated circuit includes a neural network inference circuit for executing the neural network to generate an output based on an input, an input processing circuit for providing the input to the neural network inference circuit, a microprocessor circuit for controlling the neural network inference circuit and the input processing circuit, and a unified memory accessible by the microprocessor circuit, the neural network inference circuit, and the input processing circuit. The method determines usage of the unified memory by the neural network inference circuit while executing the neural network. Based on the determined usage by the neural network inference circuit, the method allocates portions of the unified memory to the microprocessor circuit and input processing circuit.

Allocating blocks of unified memory for integrated circuit executing neural network

Some embodiments provide a method for executing a neural network. The method writes a first input to a first set of physical memory banks in a unified memory shared by an input processing circuit and a neural network inference circuit that executes the neural network. While the neural network inference circuit is executing the network a first time to generate a first output for the first input, the method writes a second input to a second set of physical memory banks in the unified memory. The neural network inference circuit executes a same set of instructions to read the first input from the first set of memory banks in order to execute the network the first time and to read the second input from the second set of memory banks in order to execute the network a second time to generate a second output for the second input.

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Los Altos, CA, United States of America

Won Rhee