About: Semi-automatic Assessment of I/O Behavior by Inspecting the Individual Client-Node Timelines—An Explorative Study on [Formula: see text] Jobs

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About: Semi-automatic Assessment of I/O Behavior by Inspecting the Individual Client-Node Timelines—An Explorative Study on [Formula: see text] Jobs Goto Sponge NotDistinct Permalink

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Semi-automatic Assessment of I/O Behavior by Inspecting the Individual Client-Node Timelines—An Explorative Study on [Formula: see text] Jobs
Creator	Betke, Eugen Kunkel, Julian
source	PMC
abstract	HPC applications with suboptimal I/O behavior interfere with well-behaving applications and lead to increased application runtime. In some cases, this may even lead to unresponsive systems and unfinished jobs. HPC monitoring systems can aid users and support staff to identify problematic behavior and support optimization of problematic applications. The key issue is how to identify relevant applications? A profile of an application doesn’t allow identifying problematic phases during the execution but tracing of each individual I/O is too invasive. In this work, we split the execution into segments, i.e., windows of fixed size and analyze profiles of them. We develop three I/O metrics to identify three relevant classes of inefficient I/O behaviors, and evaluate them on raw data of 1,000,000 jobs on the supercomputer Mistral. The advantages of our method is that temporal information about I/O activities during job runtime is preserved to some extent and can be used to identify phases of inefficient I/O. The main contribution of this work is the segmentation of time series and computation of metrics (Job-I/O-Utilization, Job-I/O-Problem-Time, and Job-I/O-Balance) that are effective to identify problematic I/O phases and jobs.
has issue date	2020-05-22(xsd:dateTime)
bibo:doi	10.1007/978-3-030-50743-5_9
has license	no-cc
sha1sum (hex)	f369024ca536a0c6eb10746350cd04e737ae52d5
schema:url	https://doi.org/10.1007/978-3-030-50743-5_9
resource representing a document's title	Semi-automatic Assessment of I/O Behavior by Inspecting the Individual Client-Node Timelines—An Explorative Study on [Formula: see text] Jobs
has PubMed Central identifier	PMC7295356
schema:publication	High Performance Computing
resource representing a document's body	covid:f369024ca536a0c6eb10746350cd04e737ae52d5#body_text
is schema:about of	named entity 'support' named entity 'users' named entity 'Inspecting' named entity 'INTERFERE' named entity 'runtime' named entity 'systems' named entity 'I/O' named entity 'I/O' named entity 'applications' named entity 'Study' named entity 'I/O' named entity 'I/O' named entity 'metadata' named entity 'I/O' named entity 'machine learning algorithms' named entity 'large-scale' named entity 'Lustre' named entity 'I/O' named entity 'parallel applications' named entity 'I/O' named entity 'high performance' named entity 'compute node' named entity 'file systems' named entity 'open source' named entity 'user-friendly' named entity 'storage systems' named entity 'compile time' named entity 'database' named entity 'I/O' named entity 'metadata' named entity 'probability' named entity 'HPC systems' named entity 'Lustre' named entity 'mathematical calculation' named entity 'POSIX' named entity 'link-time' named entity 'HDF5' named entity 'Lustre' named entity 'I/O' named entity 'OpenMPI' named entity 'I/O' named entity 'I/O' named entity 'I/O' named entity 'configuration file' named entity 'SLURM' named entity 'time series' named entity 'I/O' named entity 'HPC systems' named entity 'MVAPICH' named entity 'HPC' named entity 'Lustre' named entity 'POSIX' named entity 'I/O' named entity 'primary objective' named entity 'metadata' named entity 'I/O' named entity 'LASSi' named entity 'metadata' named entity 'I/O' named entity 'MVAPICH' named entity 'MPI' named entity 'I/O' named entity 'I/O' named entity 'I/O interfaces' named entity 'HPC' named entity 'I/O' named entity 'extreme behavior' named entity 'I/O' named entity 'I/O' named entity 'I/O' named entity 'osc' named entity 'I/O' named entity 'I/O' named entity 'I/O' named entity 'data analysis' named entity 'data acquisition' named entity 'POSIX' named entity 'job scheduling' named entity 'standard I/O' named entity 'sampling' named entity 'I/O calls' named entity 'report generator'

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