Paper

SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads

In recent years, there has been tremendous advances in hardware acceleration of deep neural networks. However, most of the research has focused on optimizing accelerator microarchitecture for higher performance and energy efficiency on a per-layer basis... (read more)

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