TY - GEN
T1 - Energy and power aware job scheduling and resource management
T2 - 32nd IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2018
AU - Maiterth, Matthias
AU - Koenig, Gregory
AU - Pedretti, Kevin
AU - Jana, Siddhartha
AU - Bates, Natalie
AU - Borghesi, Andrea
AU - Montoya, Dave
AU - Bartolini, Andrea
AU - Puzovic, Milos
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/3
Y1 - 2018/8/3
N2 - This work describes the motivation and methodology of a first-of-its-kind global survey of HPC centers actively employing Energy and Power Aware Scheduling and Resource Management solutions for their production systems. The Energy-Efficient High-Performance-Computing Working-Group (EE HPC WG) Energy and Power Aware Job Scheduling and Resource Management (EPA JSRM) team conducted comprehensive interviews over the course of 2016 and 2017. In this work, we present the selection of participating sites, the motivation behind the survey, a detailed description of the questionnaire, and illustrate why getting a global view of the ongoing efforts is a major step towards more efficient systems. Job Scheduling and Resource Management is being tackled using new approaches regarding Power and Energy and has important implications for achievable center strategies. With this survey, we are laying foundations necessary to give insights in how problems and respective solutions are approached across sites and centers to allow to identify differences, similarities, solutions, and possible technology transfer across sites and centers. Upcoming work will focus on the survey responses and the analysis thereof. At the point of writing, the EPA JSRM team is in the major analysis phase of the centers' responses. By splitting the work in this fashion we achieve increased clarity in presentation and have the opportunity to generate more detailed analysis in benevolence of the community and reader.
AB - This work describes the motivation and methodology of a first-of-its-kind global survey of HPC centers actively employing Energy and Power Aware Scheduling and Resource Management solutions for their production systems. The Energy-Efficient High-Performance-Computing Working-Group (EE HPC WG) Energy and Power Aware Job Scheduling and Resource Management (EPA JSRM) team conducted comprehensive interviews over the course of 2016 and 2017. In this work, we present the selection of participating sites, the motivation behind the survey, a detailed description of the questionnaire, and illustrate why getting a global view of the ongoing efforts is a major step towards more efficient systems. Job Scheduling and Resource Management is being tackled using new approaches regarding Power and Energy and has important implications for achievable center strategies. With this survey, we are laying foundations necessary to give insights in how problems and respective solutions are approached across sites and centers to allow to identify differences, similarities, solutions, and possible technology transfer across sites and centers. Upcoming work will focus on the survey responses and the analysis thereof. At the point of writing, the EPA JSRM team is in the major analysis phase of the centers' responses. By splitting the work in this fashion we achieve increased clarity in presentation and have the opportunity to generate more detailed analysis in benevolence of the community and reader.
KW - Computing
KW - Energy
KW - Performance
KW - Power
KW - Power-aware
KW - Scheduling
UR - http://www.scopus.com/inward/record.url?scp=85052239535&partnerID=8YFLogxK
U2 - 10.1109/IPDPSW.2018.00111
DO - 10.1109/IPDPSW.2018.00111
M3 - Conference contribution
AN - SCOPUS:85052239535
SN - 9781538655559
T3 - Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2018
SP - 685
EP - 693
BT - Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 May 2018 through 25 May 2018
ER -