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20202025
most citedDLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack

2 citations · 2 across the 5 of their papers we have counts for

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cs.AR2021

SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference

Jude Haris, Perry Gibson, José Cano +2

Edge computing devices inherently face tight resource constraints, which is especially apparent when deploying Deep Neural Networks (DNN) with high memory and compute demands. FPGA…