Result: Noise-Resilient Empirical Performance Modeling with Deep Neural Networks

*Title*:

Noise-Resilient Empirical Performance Modeling with Deep Neural Networks / Marcus Ritter, Alexander Geiß, Johannes Wehrstein, Alexandru Calotoiu, Thorsten Reimann, Torsten Hoefler, Felix Wolf

*Author/editor-in-chief*:

Ritter, Marcus (Verfasser) ; Geiß, Alexander (Verfasser) ; Wehrstein, Johannes (Verfasser) ; Calotoiu, Alexandru (Verfasser) ; Reimann, Thorsten (Verfasser) ; Hoefler, Torsten (Verfasser) ; Wolf, Felix (Verfasser)

*Published in*:

Institute of Electrical and Electronics Engineers. 2021 IEEE 35th International Parallel and Distributed Processing Symposium. - Piscataway, NJ : IEEE, 2021. - ISBN 9781665440660. - (2021), Seite 23-34

*Manufacture*:

2021

*Format*:

*eArticle*

*Language*:

*eng*

*Other edition entry*:

Erscheint auch als Druck-Ausgabe: ISBN 9781665411561

*Subject Added Keywords*:

*DOI*:

10.1109/IPDPS49936.2021.00012

*Result*: Noise-Resilient Empirical Performance Modeling with Deep Neural Networks

*Additional information*

*Additional functions*

Result: Noise-Resilient Empirical Performance Modeling with Deep Neural Networks

Additional information

Additional functions