  Stripes is a Deep Neural Network (DNN) accelerator that uses bit-serial
computation to offer performance that is proportional to the fixed-point
precision of the activation values. The fixed-point precisions are determined a
priori using profiling and are selected at a per layer granularity. This paper
presents Dynamic Stripes, an extension to Stripes that detects precision
variance at runtime and at a finer granularity. This extra level of precision
reduction increases performance by 41% over Stripes.
