Abstract
Plenty of edge deep learning accelerators are proposed to speed up the inference of deep learning algorithms on edge devices. However, Various edge deep learning accelerators feature different characteristics in terms of power and performance, which makes it a very challenging task to compare different accelerators according to their specifications and in turn prohibits a new DL model from being effectively and efficiently deployed on a suitable edge device. We introduce EDLAB, an edge deep learning accelerator benchmark tool, to evaluate the overall performance of edge deep learning accelerators. EDLAB is an end-to-end benchmark tool that provides unified workloads, deployment policy, and fair comparison methodology. Moreover, EDLAB is designed with good scalability, which can support many emerging deep learning applications and hardware.
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Recommended Citation
INC, HP, "EDLAB: A BENCHMARK TOOL FOR EDGE DEEP LEARNING ACCELERATORS", Technical Disclosure Commons, (November 20, 2020)
https://www.tdcommons.org/dpubs_series/3797