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arXiv · 1706.00504

Dynamic Stripes: Exploiting the Dynamic Precision Requirements of Activation Values in Neural Networks

Alberto Delmas·Patrick Judd·Sayeh Sharify·Andreas Moshovos
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Abstract

Stripes is a Deep Neural Network (DNN) accelerator that uses bit-serial computation to offer performance that is proportional to the fixed-point precision of the activation values. The fixed-point precisions are determined a priori using profiling and are selected at a per layer granularity. This paper presents Dynamic Stripes, an extension to Stripes that detects precision variance at runtime and at a finer granularity. This extra level of precision reduction increases performance by 41% over Stripes.

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Alberto Delmas, Patrick Judd, Sayeh Sharify, Andreas Moshovos. 2017-06-01. Dynamic Stripes: Exploiting the Dynamic Precision Requirements of Activation Values in Neural Networks. https://arxiv.org/abs/1706.00504

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