Performance prediction for convolutional neural networks on edge GPUs-Reference-Cited by-同舟云学术

Performance prediction for convolutional neural networks on edge GPUs

Published:2021-05-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 18th ACM International Conference on Computing Frontiers
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Author:

Bouzidi Halima¹,Ouarnoughi Hamza¹,Niar Smail¹,Cadi Abdessamad Ait El¹

Affiliation:

1. Université Polytechnique Hauts-de-France, Valenciennes, France

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3457388.3458666

Reference25 articles.

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2. [n.d.]. GPGPU-Sim 3.x: a cycle-level GPU performance simulator. https://github.com/gpgpu-sim/ [n.d.]. GPGPU-Sim 3.x: a cycle-level GPU performance simulator. https://github.com/gpgpu-sim/

3. [n.d.]. Harness AI at the Edge with the Jetson TX2 Developer Kit. developer.nvidia.com/embedded/jetson-tx2-developer-kit Accessed: 2018-06-30. [n.d.]. Harness AI at the Edge with the Jetson TX2 Developer Kit. developer.nvidia.com/embedded/jetson-tx2-developer-kit Accessed: 2018-06-30.

4. [n.d.]. Jetson AGX Xavier Developer Kit. developer.nvidia.com/embedded/jetson-agx-xavier-developer-kit Accessed: 2018-06-30. [n.d.]. Jetson AGX Xavier Developer Kit. developer.nvidia.com/embedded/jetson-agx-xavier-developer-kit Accessed: 2018-06-30.

5. [n.d.]. Multi2Sim: A Heterogeneous System Simulator. http://www.multi2sim.org/ [n.d.]. Multi2Sim: A Heterogeneous System Simulator. http://www.multi2sim.org/

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