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FloatPIM

Published • Jun 14, 2019
Authors:
Mohsen Imani
,
Saransh Gupta
,
Yeseong Kim

Abstract

Processing In-Memory (PIM) has shown a great potential to accelerate inference tasks of Convolutional Neural Network (CNN). However, existing PIM architectures do not support high precision computation, e.g., in floating point precision, which is essential for training accurate CNN models. In additi...

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