DPRed: Making Typical Activation and Weight Values Matter In Deep Learning Computing

17 Apr 2018Alberto DelmasSayeh SharifyPatrick JuddKevin SiuMilos NikolicAndreas Moshovos

We show that selecting a single data type (precision) for all values in Deep Neural Networks, even if that data type is different per layer, amounts to worst case design. Much shorter data types can be used if we target the common case by adjusting the precision at a much finer granularity... (read more)

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