Microsoft Corporation
EXECUTION OF DEEP-LEARNING MODEL

Abstract:

In accordance with implementations of the subject matter described herein, there is provided a solution for execution of a deep learning model. In the solution, partitioned convolutions are executed based on an input and a set of parameter values of the convolutional layer sequentially in a trusted execution environment (TEE) of a computing device. The execution of a given one of partitioned convolutions comprises: storing, into a protected memory area in the TEE, an input portion of the input to be processed by a subset of parameter values for the given partitioned convolution; determining a result of the given partitioned convolution through a single matrix multiplication operation; and removing the input portion. By combining results of the partitioned convolutions, a result of the convolution is determined. Therefore, the solution can accelerate the model execution speed and improve the storage efficiency in a highly safe TEE with limited memory resources.