A graph neural network-based performance model for deep learning applications-Reference-Cited by-同舟云学术

A graph neural network-based performance model for deep learning applications

Published:2022-06-13 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming
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Author:

Singh Shikhar¹,Hegarty James¹,Leather Hugh¹,Steiner Benoit¹

Affiliation:

1. Meta, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3520312.3534863

Reference23 articles.

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3. [n.d.]. Halide Tutorial: Scheduling multi-stage pipelines. https://halide-lang.org/docs/tutorial_2lesson_08_scheduling_2_8cppexample.html [n.d.]. Halide Tutorial: Scheduling multi-stage pipelines. https://halide-lang.org/docs/tutorial_2lesson_08_scheduling_2_8cppexample.html

4. [n.d.]. Open Neural Network Exchange. https://onnx.ai/. Accessed: 2020-06-15. [n.d.]. Open Neural Network Exchange. https://onnx.ai/. Accessed: 2020-06-15.

5. [n.d.]. oneAPI Deep Neural Network Library (oneDNN). https:// github.com/oneapi-src/oneDNN. Accessed: 2021-08-19. [n.d.]. oneAPI Deep Neural Network Library (oneDNN). https:// github.com/oneapi-src/oneDNN. Accessed: 2021-08-19.

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