Eyeriss: A Spatial Architecture for Energy-Efficient Dataflow for Convolutional Neural Networks
Deep convolutional neural networks (CNNs) are widely used in modern AI systems for their superior accuracy but at the cost of high computational complexity. The complexity comes from the need to simultaneously process hundreds of filters and channels in the high-dimensional convolutions, which invol...
Main Authors: | Chen, Yu-Hsin (Contributor), Emer, Joel S. (Contributor), Sze, Vivienne (Contributor) |
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Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor) |
Format: | Article |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers (IEEE),
2016-05-03T01:15:11Z.
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Subjects: | |
Online Access: | Get fulltext |
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