SF-MMCN: A Low Power Re-configurable Server Flow Convolution Neural Network Accelerator

arXiv:2403.10542v1 Announce Type: cross
Abstract: Convolution Neural Network (CNN) accelerators have been developed rapidly in recent studies. There are lots of CNN accelerators equipped with a variety of function and algorithm which results in low power and high-speed performances. However, the scale of a PE array in traditional CNN accelerators is too big, which costs the most energy consumption while conducting multiply and accumulation (MAC) computations. The other issue is that due to the advance of CNN models, there are …

abstract accelerator accelerators algorithm array arxiv cnn convolution convolution neural network cs.ar cs.cv flow function however low low power network neural network performances power results scale server speed studies type