A Simple Method to Reduce Off-chip Memory Accesses on Convolutional Neural Networks

Doyun Kim; Kyoung-Young Kim; Sangsoo Ko; Sanghyuck Ha

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arXiv · 1901.09614

A Simple Method to Reduce Off-chip Memory Accesses on Convolutional Neural Networks

Doyun Kim·Kyoung-Young Kim·Sangsoo Ko·Sanghyuck Ha

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Abstract

For convolutional neural networks, a simple algorithm to reduce off-chip memory accesses is proposed by maximally utilizing on-chip memory in a neural process unit. Especially, the algorithm provides an effective way to process a module which consists of multiple branches and a merge layer. For Inception-V3 on Samsung's NPU in Exynos, our evaluation shows that the proposed algorithm makes off-chip memory accesses reduced by 1/50, and accordingly achieves 97.59 % reduction in the amount of feature-map data to be transferred from/to off-chip memory.

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Doyun Kim, Kyoung-Young Kim, Sangsoo Ko, Sanghyuck Ha. 2019-01-28. A Simple Method to Reduce Off-chip Memory Accesses on Convolutional Neural Networks. https://arxiv.org/abs/1901.09614

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