Google Neural Network Models for Edge Devices: Analyzing and Mitigating Machine Learning Inference Bottlenecks

Emerging edge computing platforms often contain machine learning (ML) accelerators that can accelerate inference for a wide range of neural network (NN) models. These models are designed to fit within the limited area and energy constraints of the edge computing platforms, each targeting various app...

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Bibliographische Detailangaben

Veröffentlicht in:	2021 30th International Conference on Parallel Architectures and Compilation Techniques (PACT) S. 159 - 172
Hauptverfasser:	Boroumand, Amirali, Ghose, Saugata, Akin, Berkin, Narayanaswami, Ravi, Oliveira, Geraldo F., Ma, Xiaoyu, Shiu, Eric, Mutlu, Onur
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.09.2021
Schlagworte:	Analytical models Artificial neural networks Computational modeling Image edge detection Machine learning Throughput Visual analytics
Online-Zugang:	Volltext
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