2019
DOI: 10.48550/arxiv.1910.10794
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Sidebar: Scratchpad Based Communication Between CPUs and Accelerators

Abstract: Hardware accelerators for neural networks have shown great promise for both performance and power. These accelerators are at their most efficient when optimized for a fixed functionality. But this inflexibility limits the longevity of the hardware itself as the underlying neural network algorithms and structures undergo improvements and changes. We propose and evaluate a flexible design paradigm for accelerators with a close coordination with host processors. The relatively static matrix operations are impleme… Show more

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