Paper Abstract and Keywords |
Presentation |
2021-04-15 13:50
Estimation of server power consumption using machine learning
-- In the case of disk intensive workload -- Katsumi Fujita, Eriko Iwasa, Masashi Kaneko (NTT) NS2021-6 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
A server power consumption is one of the problem in a data center. There are virtualization and DVFS approaches to address this problem. Estimating power consumption of servers is necessary for these approaches. Previous works presented server power models for CPU and memory intensive workloads. In this paper, we focused on disk intensive workloads and built the server power model by machine learning. Our method used processor performance events as input data. This model is applicable to a server power estimation for disk intensive workload. Moreover we analyzed the feature importance and found that different server power models are needed depending on the type of workloads. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
server / power consumption / machine learning / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 2, NS2021-6, pp. 31-36, April 2021. |
Paper # |
NS2021-6 |
Date of Issue |
2021-04-08 (NS) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NS2021-6 |
Conference Information |
Committee |
NS |
Conference Date |
2021-04-15 - 2021-04-16 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Traffic, Network evaluation, Performance, Resource control and management, Traffic engineering, Network reliability and resilience, Network Intelligence and AI, etc. |
Paper Information |
Registration To |
NS |
Conference Code |
2021-04-NS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Estimation of server power consumption using machine learning |
Sub Title (in English) |
In the case of disk intensive workload |
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server |
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power consumption |
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machine learning |
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1st Author's Name |
Katsumi Fujita |
1st Author's Affiliation |
NTT (NTT) |
2nd Author's Name |
Eriko Iwasa |
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NTT (NTT) |
3rd Author's Name |
Masashi Kaneko |
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NTT (NTT) |
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Speaker |
Author-1 |
Date Time |
2021-04-15 13:50:00 |
Presentation Time |
25 minutes |
Registration for |
NS |
Paper # |
NS2021-6 |
Volume (vol) |
vol.121 |
Number (no) |
no.2 |
Page |
pp.31-36 |
#Pages |
6 |
Date of Issue |
2021-04-08 (NS) |
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