Titlebook: Number Systems for Deep Neural Network Architectures; Ghada Alsuhli,Vasilis Sakellariou,Thanos Stouraiti Book 2024 The Editor(s) (if appli

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,RNS for?DNN Architectures, of which are multiply-add operations. These operations can be very efficiently implemented in the Residue Numbering System: RNS encoding allows for carry-free computations among the different residue channels, with inherent parallelism at the digit processing level. Arithmetic circuits for addition

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,BFP for?DNN Architectures, in deep neural network implementations. We begin by providing an overview of BFP and explaining how it differs from FLP and FXP. Next, we discuss the factors that can impact the performance of BFP in DNN acceleration, drawing from existing literature to identify the best practices for optimizing BF

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