Micron Technology, Inc.
OPTIMIZED SENSOR FUSION IN DEEP LEARNING ACCELERATOR WITH INTEGRATED RANDOM ACCESS MEMORY

Abstract:

Systems, devices, and methods related to a Deep Learning Accelerator and memory are described. For example, an integrated circuit device may be configured to execute instructions with matrix operands and configured with random access memory. The random access memory is configured to store a plurality of inputs from a plurality of sensors respective, parameters of an Artificial Neural Network, and instructions executable by the Deep Learning Accelerator to perform matrix computation to generate outputs of the Artificial Neural Network, including first outputs generated using the sensors separately and a second output generated using a combination of the sensors.