Abstract: This research introduces a novel Processing Engine (PE) for convolution layers in Deep Neural Network (DNN) accelerators. The PE integrates multi-precision dynamic fraction fixed-point ...
Abstract: The Multiply and Accumulator (MAC) in Convolution Neural Network (CNN) for image applications demands an efficient matrix multiplier. This study presents an area- and power-efficient ...
Abstract: In-network computing leverages computational capabilities of network nodes themselves to enable real-time data processing along the transmission path, further shortening the distance between ...
Abstract: Acupuncture point location information is significant to the effect of acupuncture therapy. A wealth of knowledge related to acupuncture point locations is typically dispersed across books ...
Abstract: The increasing energy consumption of manufacturing companies has placed a lot of pressure on the power grid. To alleviate the pressure and flatten the demand peaks over a day, time-of-use ...
Abstract: A precision-scalable neural processing unit, considering the quantization-sensitive of each neural network layer, has large hardware redundancy in multiplication units and shift logics. In ...
Abstract: Hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) parallel programs are pivotal for scalability and efficiency in high-performance computing (HPC), especially as ...
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