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Dataset . 2023
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Dataset . 2023
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M100 dataset 2: from 21-01 to 21-06

Authors: Borghesi, Andrea; Di Santi, Carmine; Molan, Martin; Ardebili, Mohsen Seyedkazemi; Mauri, Alessio; Guarrasi, Massimiliano; Galetti, Daniela; +5 Authors

M100 dataset 2: from 21-01 to 21-06

Abstract

This entry is a part of a larger data set collected from the most recent Tier-0 supercomputer hosted at CINECA (Marconi100, https://www.hpc.cineca.it/hardware/marconi100). The data covers the entirety of the system, ranging from the computing nodes (980+ computing nodes) internal information such as core loads, temperatures, frequencies, memory write/read operations, CPU power consumption, fan speed, GPU usage details, etc., to the system-wide information, including the liquid cooling infrastructure, the air conditioning system, the power supply units, workload manager statistics, and job-related information, system status alerts, and weather forecast. It comprises hundreds of metrics measured on each computing node, in addition to hundreds of other metrics gathered from sensors monitored along all system components. The whole data set is stored as a collection of Zenodo entries; this particular entry corresponds to the period: 21-01, 21-06. The dataset is stored as a partitioned Parquet dataset, with this partitioning hierarchy: year_month ("YY-MM"), plugin, metric. The data is distributed as tarball files, each corresponding to one month of data (first-level partitioning, year_month). The collected data is generated by a monitoring infrastructure working on unstructured data (to improve efficiency and scalability); however, this data has been organized in a structured manner to facilitate its fruition. The simplest way to understand how the access the data is to refer to the companion software modules released together with the dataset itself, which can be found at: https://gitlab.com/ecs-lab/exadata.

Keywords

HPC, Supercomputing, Datacenter, High-performance computing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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