NDLI: Improving Preemptive Scheduling with Application-Transparent Checkpointing in Shared Clusters

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Improving Preemptive Scheduling with Application-Transparent Checkpointing in Shared Clusters

Content Provider	ACM Digital Library
Author	Talwar, Vanish Milojicic, Dejan Li, Jack Pu, Calton Chen, Yuan
Abstract	Modern data center clusters are shifting from dedicated single framework clusters to shared clusters. In such shared environments, cluster schedulers typically utilize preemption by simply killing jobs in order to achieve resource priority and fairness during peak utilization. This can cause significant resource waste and delay job response time. In this paper, we propose using suspend-resume mechanisms to mitigate the overhead of preemption in cluster scheduling. Instead of killing preempted jobs or tasks, our approach uses a system level, application-transparent checkpointing mechanism to save the progress of jobs for resumption at a later time when resources are available. To reduce the preemption overhead and improve job response times, our approach uses adaptive preemption to dynamically select appropriate preemption mechanisms (e.g., kill vs. suspend, local vs. remote restore) according to the progress of a task and its suspend-resume overhead. By leveraging fast storage technologies, such as non-volatile memory (NVM), our approach can further reduce the preemption penalty to provide better QoS and resource efficiency. We implement the proposed approach and conduct extensive experiments via Google cluster trace-driven simulations and applications on a Hadoop cluster. The results demonstrate that our approach can significantly reduce the resource and power usage and improve application performance over existing approaches. In particular, our implementation on the next generation Hadoop YARN platform achieves up to a 67% reduction in resource wastage, 30% improvement in overall job response time times and 34% reduction in energy consumption over the current YARN scheduler.
Starting Page	222
Ending Page	234
Page Count	13
File Format	PDF
ISBN	9781450336185
DOI	10.1145/2814576.2814807
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-11-24
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Cloud computing Cluster resource management Scheduling
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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