Predicting Inference Latency of Neural Architectures on Mobile Devices

Author:

Li Zhuojin1ORCID,Paolieri Marco1ORCID,Golubchik Leana1ORCID

Affiliation:

1. University of Southern California, Los Angeles, CA, USA

Funder

NSF

Publisher

ACM

Reference69 articles.

1. MAPLE: Microprocessor A Priori for Latency Estimation

2. Apple. 2016. Prioritize Work at the Task Level. https://developer.apple.com/library/archive/documentation/Performance/Conceptual/power_efficiency_guidelines_osx/PrioritizeWorkAtTheTaskLevel.html Accessed: 2022--10--10. Apple. 2016. Prioritize Work at the Task Level. https://developer.apple.com/library/archive/documentation/Performance/Conceptual/power_efficiency_guidelines_osx/PrioritizeWorkAtTheTaskLevel.html Accessed: 2022--10--10.

3. Apple. 2021. Discover Metal debugging profiling and asset creation tools. https://developer.apple.com/videos/play/wwdc2021/10157 Accessed: 2022--10-06. Apple. 2021. Discover Metal debugging profiling and asset creation tools. https://developer.apple.com/videos/play/wwdc2021/10157 Accessed: 2022--10-06.

4. Execution Time Modeling for CNN Inference on Embedded GPUs

5. Performance prediction for convolutional neural networks on edge GPUs

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