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Thamsen et al., 2019 - Google Patents

Hugo: a cluster scheduler that efficiently learns to select complementary data-parallel jobs

Thamsen et al., 2019

View PDF
Document ID
6046429479513948198
Author
Thamsen L
Verbitskiy I
Nedelkoski S
Tran V
Meyer V
Xavier M
Kao O
De Rose C
Publication year
Publication venue
European Conference on Parallel Processing

External Links

Snippet

Distributed data processing systems like MapReduce, Spark, and Flink are popular tools for analysis of large datasets with cluster resources. Yet, users often overprovision resources for their data processing jobs, while the resource usage of these jobs also typically fluctuates …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

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    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Programme initiating; Programme switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
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    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
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    • G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
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    • G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
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