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Found 4 papers, 2 papers with code
Flexible Channel Dimensions for Differentiable Architecture Search
Finding optimal channel dimensions (i. e., the number of filters in DNN layers) is essential to design DNNs that perform well under computational resource constraints.
Hierarchical Training of Deep Neural Networks Using Early Exiting
In this study, a novel hierarchical training method for deep neural networks is proposed that uses early exits in a divided architecture between edge and cloud workers to reduce the communication cost, training runtime and privacy concerns.
U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search
Optimizing resource utilization in target platforms is key to achieving high performance during DNN inference.
Hardware Aware Neural Architecture Search
Image Classification
+1
Scale-out Systolic Arrays
In this work, we study three key pillars in multi-pod systolic array designs, namely array granularity, interconnect, and tiling.
