International Business Machines Corporation
Optimal placement of data structures in a hybrid memory based inference computing platform

Abstract:

In a deep neural network (DNN), weights are defined that represent a strength of connections between different neurons of the DNN and activations are defined that represent an output produced by a neuron after passing through an activation function of receiving an input and producing an output based on some threshold value. The weight traffic associated with a hybrid memory therefore is distinguished from the activation traffic to the hybrid memory, and one or more data structures may be dynamically allocated in the hybrid memory according to the weights and activations of the one or more data structures in the DNN. The hybrid memory includes at least a first memory and a second memory that differ according to write endurance attributes.