Energy-efficiency of OWL reasoners—frequency matters

Patrick Koopmann; Marcus Hähnel; Anni-Yasmin Turhan

doi:10.1007/978-3-319-70682-5_6

Energy-efficiency of OWL reasoners—frequency matters

Patrick Koopmann
, Marcus Hähnel
, Anni-Yasmin Turhan

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

While running times of ontology reasoners have been studied extensively, studies on energy-consumption of reasoning are scarce, and the energy-efficiency of ontology reasoning is not fully understood yet. Earlier empirical studies on the energy-consumption of ontology reasoners focused on reasoning on smart phones and used measurement methods prone to noise and side-effects. This paper presents an evaluation of the energy-efficiency of five state-of-the-art OWL reasoners on an ARM single-board computer that has built-in sensors to measure the energy consumption of CPUs and memory precisely. Using such a machine gives full control over installed and running software, active clusters and CPU frequencies, allowing for a more precise and detailed picture of the energy consumption of ontology reasoning. Besides evaluating the energy consumption of reasoning, our study further explores the relationship between computation power of the CPU, reasoning time, and energy consumption.

Original language	English
Title of host publication	Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings
Editors	Z. Wang, K. Wang, A.-Y. Turhan, X. Zhang
Publisher	Springer Verlag
Pages	86-101
ISBN (Print)	9783319706818
DOIs	https://doi.org/10.1007/978-3-319-70682-5_6
Publication status	Published - 2017
Externally published	Yes
Event	7th Joint International Conference on Semantic Technology, JIST 2017 - Gold Coast, Australia Duration: 10 Nov 2017 → 12 Nov 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th Joint International Conference on Semantic Technology, JIST 2017
Country/Territory	Australia
City	Gold Coast
Period	10/11/17 → 12/11/17

Funding

This work is supported (in part) by the German Research Foundation (DFG) within the Collaborative Research Center SFB 912 HAEC.

Funders	Funder number
DFG	SFB 912 HAEC
German Research Foundation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Access to Document

10.1007/978-3-319-70682-5_6

Persistent URL (handle)

Persistent link

Cite this

Koopmann, P., Hähnel, M., & Turhan, A.-Y. (2017). Energy-efficiency of OWL reasoners—frequency matters. In Z. Wang, K. Wang, A.-Y. Turhan, & X. Zhang (Eds.), Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings (pp. 86-101). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Springer Verlag. https://doi.org/10.1007/978-3-319-70682-5_6

Koopmann, Patrick ; Hähnel, Marcus ; Turhan, Anni-Yasmin. / Energy-efficiency of OWL reasoners—frequency matters. Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings. editor / Z. Wang ; K. Wang ; A.-Y. Turhan ; X. Zhang. Springer Verlag, 2017. pp. 86-101 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Energy-efficiency of OWL reasoners—frequency matters",

abstract = "While running times of ontology reasoners have been studied extensively, studies on energy-consumption of reasoning are scarce, and the energy-efficiency of ontology reasoning is not fully understood yet. Earlier empirical studies on the energy-consumption of ontology reasoners focused on reasoning on smart phones and used measurement methods prone to noise and side-effects. This paper presents an evaluation of the energy-efficiency of five state-of-the-art OWL reasoners on an ARM single-board computer that has built-in sensors to measure the energy consumption of CPUs and memory precisely. Using such a machine gives full control over installed and running software, active clusters and CPU frequencies, allowing for a more precise and detailed picture of the energy consumption of ontology reasoning. Besides evaluating the energy consumption of reasoning, our study further explores the relationship between computation power of the CPU, reasoning time, and energy consumption.",

author = "Patrick Koopmann and Marcus H{\"a}hnel and Anni-Yasmin Turhan",

year = "2017",

doi = "10.1007/978-3-319-70682-5\_6",

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editor = "Z. Wang and K. Wang and A.-Y. Turhan and X. Zhang",

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Koopmann, P, Hähnel, M & Turhan, A-Y 2017, Energy-efficiency of OWL reasoners—frequency matters. in Z Wang, K Wang, A-Y Turhan & X Zhang (eds), Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, pp. 86-101, 7th Joint International Conference on Semantic Technology, JIST 2017, Gold Coast, Australia, 10/11/17. https://doi.org/10.1007/978-3-319-70682-5_6

Energy-efficiency of OWL reasoners—frequency matters. / Koopmann, Patrick; Hähnel, Marcus; Turhan, Anni-Yasmin.
Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings. ed. / Z. Wang; K. Wang; A.-Y. Turhan; X. Zhang. Springer Verlag, 2017. p. 86-101 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Energy-efficiency of OWL reasoners—frequency matters

AU - Koopmann, Patrick

AU - Hähnel, Marcus

AU - Turhan, Anni-Yasmin

PY - 2017

Y1 - 2017

N2 - While running times of ontology reasoners have been studied extensively, studies on energy-consumption of reasoning are scarce, and the energy-efficiency of ontology reasoning is not fully understood yet. Earlier empirical studies on the energy-consumption of ontology reasoners focused on reasoning on smart phones and used measurement methods prone to noise and side-effects. This paper presents an evaluation of the energy-efficiency of five state-of-the-art OWL reasoners on an ARM single-board computer that has built-in sensors to measure the energy consumption of CPUs and memory precisely. Using such a machine gives full control over installed and running software, active clusters and CPU frequencies, allowing for a more precise and detailed picture of the energy consumption of ontology reasoning. Besides evaluating the energy consumption of reasoning, our study further explores the relationship between computation power of the CPU, reasoning time, and energy consumption.

AB - While running times of ontology reasoners have been studied extensively, studies on energy-consumption of reasoning are scarce, and the energy-efficiency of ontology reasoning is not fully understood yet. Earlier empirical studies on the energy-consumption of ontology reasoners focused on reasoning on smart phones and used measurement methods prone to noise and side-effects. This paper presents an evaluation of the energy-efficiency of five state-of-the-art OWL reasoners on an ARM single-board computer that has built-in sensors to measure the energy consumption of CPUs and memory precisely. Using such a machine gives full control over installed and running software, active clusters and CPU frequencies, allowing for a more precise and detailed picture of the energy consumption of ontology reasoning. Besides evaluating the energy consumption of reasoning, our study further explores the relationship between computation power of the CPU, reasoning time, and energy consumption.

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SN - 9783319706818

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings

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PB - Springer Verlag

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Koopmann P, Hähnel M, Turhan AY. Energy-efficiency of OWL reasoners—frequency matters. In Wang Z, Wang K, Turhan AY, Zhang X, editors, Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings. Springer Verlag. 2017. p. 86-101. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-70682-5_6

Energy-efficiency of OWL reasoners—frequency matters

Abstract

Publication series

Conference

Funding

UN SDGs

Access to Document

Persistent URL (handle)

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Cite this