MATIC: Learning Around Errors for Efficient Low-Voltage Neural Network Accelerators

14 Jun 2017Sung KimPatrick HoweThierry MoreauArmin AlaghiLuis CezeVisvesh Sathe

As a result of the increasing demand for deep neural network (DNN)-based services, efforts to develop dedicated hardware accelerators for DNNs are growing rapidly. However,while accelerators with high performance and efficiency on convolutional deep neural networks (Conv-DNNs) have been developed, less progress has been made with regards to fully-connected DNNs (FC-DNNs)... (read more)

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