CoDR: Computation and Data Reuse Aware CNN Accelerator
TimeTuesday, December 7th6:00pm - 7:00pm PST
LocationLevel 2 - Lobby
DescriptionComputation and Data Reuse is critical for the resource-limited Convolutional Neural Network (CNN) accelerators. This paper presents Universal Computation Reuse to exploit weight sparsity, repetition, and similarity simultaneously in a convolutional layer. Moreover, CoDR decreases the cost of weight memory access by proposing a customized Run-Length Encoding scheme and the number of memory accesses to the intermediate results by introducing an input and output stationary dataflow. Compared to two recent compressed CNN accelerators  with the same area of 2.85 mm2, CoDR decreases SRAM access by 5.08X and 7.99X, and consumes 3.76X and 6.84X less energy.