Online Testing of a Row-Stationary Convolution Accelerator

摘要

Convolution accelerators used in safety-critical systems require robustness and resilience to runtime faults. In this paper, we design a processing element for the convolution accelerators that support a row-stationary dataflow. The proposed processing element is equipped with an embedded built-in mechanism for online testing of its computational parts without degrading performance by taking advantage of CNN data sparsity. Furthermore, the proposed architecture uses a low-cost error-detecting code to verify PE interconnections and local memory. The result obtained using post-synthesis simulations reveal, on average, 34% and 30% overheads on the power and area, respectively. This is in exchange for equipping the architecture with components that detect and locate faulty processing elements at runtime.