Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
High-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs t...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/16/2/890 |
| _version_ | 1797443119367585792 |
|---|---|
| author | Bartłomiej Kocot Paweł Czarnul Jerzy Proficz |
| author_facet | Bartłomiej Kocot Paweł Czarnul Jerzy Proficz |
| author_sort | Bartłomiej Kocot |
| collection | DOAJ |
| description | High-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the problem definition, tackling various goals set up for this challenge, including a bi-objective approach, power and energy constraints, and a pure energy solution, as well as metrics related to the subject. Then, considered types of HPC systems and related energy-saving mechanisms are described, from multicore-processors/graphical processing units (GPU) to more complex solutions, such as compute clusters supporting dynamic voltage and frequency scaling (DVFS), power capping, and other functionalities. The main section presents a collection of carefully selected algorithms, classified by the programming method, e.g., machine learning or fuzzy logic. Moreover, other surveys published on this subject are summarized and commented on, and finally, an overview of the current state-of-the-art with open problems and further research areas is presented. |
| first_indexed | 2024-03-09T12:51:26Z |
| format | Article |
| id | doaj.art-e560ed826c8f4ad3b6f5a3bb62664729 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T12:51:26Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-e560ed826c8f4ad3b6f5a3bb626647292023-11-30T22:05:33ZengMDPI AGEnergies1996-10732023-01-0116289010.3390/en16020890Energy-Aware Scheduling for High-Performance Computing Systems: A SurveyBartłomiej Kocot0Paweł Czarnul1Jerzy Proficz2Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdańsk, PolandDepartment of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdańsk, PolandCentre of Informatics—Tricity Academic Supercomputer & Network (CI TASK), Gdansk University of Technology, 80-233 Gdańsk, PolandHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the problem definition, tackling various goals set up for this challenge, including a bi-objective approach, power and energy constraints, and a pure energy solution, as well as metrics related to the subject. Then, considered types of HPC systems and related energy-saving mechanisms are described, from multicore-processors/graphical processing units (GPU) to more complex solutions, such as compute clusters supporting dynamic voltage and frequency scaling (DVFS), power capping, and other functionalities. The main section presents a collection of carefully selected algorithms, classified by the programming method, e.g., machine learning or fuzzy logic. Moreover, other surveys published on this subject are summarized and commented on, and finally, an overview of the current state-of-the-art with open problems and further research areas is presented.https://www.mdpi.com/1996-1073/16/2/890high-performance computingenergy-aware schedulingenergy-aware metricsDVFSpower capping |
| spellingShingle | Bartłomiej Kocot Paweł Czarnul Jerzy Proficz Energy-Aware Scheduling for High-Performance Computing Systems: A Survey Energies high-performance computing energy-aware scheduling energy-aware metrics DVFS power capping |
| title | Energy-Aware Scheduling for High-Performance Computing Systems: A Survey |
| title_full | Energy-Aware Scheduling for High-Performance Computing Systems: A Survey |
| title_fullStr | Energy-Aware Scheduling for High-Performance Computing Systems: A Survey |
| title_full_unstemmed | Energy-Aware Scheduling for High-Performance Computing Systems: A Survey |
| title_short | Energy-Aware Scheduling for High-Performance Computing Systems: A Survey |
| title_sort | energy aware scheduling for high performance computing systems a survey |
| topic | high-performance computing energy-aware scheduling energy-aware metrics DVFS power capping |
| url | https://www.mdpi.com/1996-1073/16/2/890 |
| work_keys_str_mv | AT bartłomiejkocot energyawareschedulingforhighperformancecomputingsystemsasurvey AT pawełczarnul energyawareschedulingforhighperformancecomputingsystemsasurvey AT jerzyproficz energyawareschedulingforhighperformancecomputingsystemsasurvey |