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Published in 2019 at "IEEE Transactions on Very Large Scale Integration (VLSI) Systems"
DOI: 10.1109/tvlsi.2019.2897052
Abstract: Although the existing single-instruction–multiple-data-like (SIMD) accelerators can handle the compressed format of sparse convolutional neural networks, the sparse and irregular distributions of nonzero elements cause low utilization of multipliers in a processing engine (PE) and…
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Keywords:
like accelerator;
neural networks;
accelerator;
sparse convolutional ... See more keywords