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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