Lane Shared Bit Pragmatic Deep Neural Network Computing Architecture and Circuit

It is critical to continously improve the hardware efficiency of deep neural network accelerators for its application on resource constrained platform. This paper proposes a lane shared bit-pragmatic architecture to address the synchronization induced performance bottleneck and hence further improve the performance and efficiency of bit-serial computing architecture. The effectiveness and efficiency of the proposed architecture are demonstrated by extensive evaluation results.