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Fair Resource Allocation for Running HPC Workloads Simultaneously. / Kuchumov, Ruslan; Korkhov, Vladimir.

в: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том 11622, 01.07.2019, стр. 740-751.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Kuchumov, R & Korkhov, V 2019, 'Fair Resource Allocation for Running HPC Workloads Simultaneously', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 11622, стр. 740-751. https://doi.org/10.1007/978-3-030-24305-0_55

APA

Kuchumov, R., & Korkhov, V. (2019). Fair Resource Allocation for Running HPC Workloads Simultaneously. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11622, 740-751. https://doi.org/10.1007/978-3-030-24305-0_55

Vancouver

Kuchumov R, Korkhov V. Fair Resource Allocation for Running HPC Workloads Simultaneously. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019 Июль 1;11622:740-751. https://doi.org/10.1007/978-3-030-24305-0_55

Author

Kuchumov, Ruslan ; Korkhov, Vladimir. / Fair Resource Allocation for Running HPC Workloads Simultaneously. в: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019 ; Том 11622. стр. 740-751.

BibTeX

@article{253c5a3a493c4ce8bb2d62bcc441705f,
title = "Fair Resource Allocation for Running HPC Workloads Simultaneously",
abstract = "In high performance computing (HPC) job schedulers usually divide resources of computing nodes into slots. Each slot can be assigned to execute only a single job from the queue. In some cases, jobs do not fully utilize all available resources from the slot which leads to internal fragmentation, wasted resources and to an increase of queue wait time. In this paper, we propose fair resource allocation strategies that can be applied in job schedulers for resource allocation. We cover such resources as CPU time, residential memory and network bandwidth.",
keywords = "Fair resource allocation, High performance computing, Scheduling",
author = "Ruslan Kuchumov and Vladimir Korkhov",
year = "2019",
month = jul,
day = "1",
doi = "10.1007/978-3-030-24305-0_55",
language = "English",
volume = "11622",
pages = "740--751",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Nature",
note = "19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference date: 01-07-2019 Through 04-07-2019",

}

RIS

TY - JOUR

T1 - Fair Resource Allocation for Running HPC Workloads Simultaneously

AU - Kuchumov, Ruslan

AU - Korkhov, Vladimir

N1 - Conference code: 19

PY - 2019/7/1

Y1 - 2019/7/1

N2 - In high performance computing (HPC) job schedulers usually divide resources of computing nodes into slots. Each slot can be assigned to execute only a single job from the queue. In some cases, jobs do not fully utilize all available resources from the slot which leads to internal fragmentation, wasted resources and to an increase of queue wait time. In this paper, we propose fair resource allocation strategies that can be applied in job schedulers for resource allocation. We cover such resources as CPU time, residential memory and network bandwidth.

AB - In high performance computing (HPC) job schedulers usually divide resources of computing nodes into slots. Each slot can be assigned to execute only a single job from the queue. In some cases, jobs do not fully utilize all available resources from the slot which leads to internal fragmentation, wasted resources and to an increase of queue wait time. In this paper, we propose fair resource allocation strategies that can be applied in job schedulers for resource allocation. We cover such resources as CPU time, residential memory and network bandwidth.

KW - Fair resource allocation

KW - High performance computing

KW - Scheduling

UR - http://www.scopus.com/inward/record.url?scp=85068620987&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-24305-0_55

DO - 10.1007/978-3-030-24305-0_55

M3 - Article

AN - SCOPUS:85068620987

VL - 11622

SP - 740

EP - 751

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

T2 - 19th International Conference on Computational Science and Its Applications, ICCSA 2019

Y2 - 1 July 2019 through 4 July 2019

ER -

ID: 44017004