Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)

Quantifying the Influences of Data Prefetching Using Artificial Neural Networks

Authors
Kecheng Ji, Li Liu
Corresponding Author
Kecheng Ji
Available Online March 2018.
DOI
https://doi.org/10.2991/acaai-18.2018.40How to use a DOI?
Keywords
cache misses; data prefetching; artificial neural networks
Abstract

Data prefetching has been widely used in modern cache subsystems. Actually, an aggressive prefetching may bring negative yields unexpectedly, in which a new proposed prefetching strategy normally needs to be evaluated before being applied in the real design. In the last decade, prior researchers prefer to utilize the cycle-accurate simulations or trace-driven simulations to study the prefetching behaviors. However, as the increasing complexity of hardware components, the huge time-consuming simulation-based methods would never be appropriate for performance evaluations. This paper proposes a method of modeling prefetching influences on cache misses using artificial neural networks, which has an average error of 8% compared to gem5 cycle-accurate simulations, and the performance prediction process can be sped up by 30 times on average.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
Series
Advances in Intelligent Systems Research
Publication Date
March 2018
ISBN
978-94-6252-483-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/acaai-18.2018.40How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Kecheng Ji
AU  - Li Liu
PY  - 2018/03
DA  - 2018/03
TI  - Quantifying the Influences of Data Prefetching Using Artificial Neural Networks
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 170
EP  - 172
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.40
DO  - https://doi.org/10.2991/acaai-18.2018.40
ID  - Ji2018/03
ER  -