Exploring Winograd Convolution for Cost-effective Neural Network Fault Tolerance

Xinghua Xue, Cheng Liu, Bo Liu +6

Winograd is generally utilized to optimize convolution performance and computational efficiency because of the reduced multiplication operations, but the reliability issues brought…