Data shuffle optimization

Abstract

An optimization algorithm is disclosed to reduce the number of data shuffle operators in a data flow graph representing a neural network model for a neural network. The optimization algorithm can identify single-entry single-exit (SESE) regions in the data flow graph and select the SESE regions that comprise only the data shuffle operators. An affine map for each selected SESE region can be generated from an input of the selected SESE region to an output of the selected SESE region. An affine shuffle operator corresponding to an affine map for a selected SESE region can replace that SESE region if an implementation cost of the affine map is lower than the implementation cost of the SESE region. Thus, by replacing the selected SESE regions comprising multiple data shuffle operators with corresponding affine shuffle operators, it is possible to reduce the total number of operators in the data flow graph and optimize the neural network model.

CPC Classifications