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Dataset . 2023
License: CC BY
Data sources: Datacite
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Dataset . 2023
License: CC BY
Data sources: Datacite
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Dataset . 2023
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https://doi.org/10.5281/zenodo...
Dataset . 2023
License: CC BY
Data sources: Sygma
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M100 dataset: time-aggregated data for anomaly detection

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

M100 dataset: time-aggregated data for anomaly detection

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. This particular dataset is made for anomaly detection purposes, it contains the same data as the main dataset but aggregated over time, with one Parquet file for each node. The data is distributed in tarballs, each one including all the files relative to the nodes contained in a given rack. For each file, the rows represent periods of 15 minutes, with the columns being aggregated values (average, standard deviation, min, max) over all the IPMI metrics that are available for the node; an additional column contains anomaly labels from Nagios. More details can be found in the companion repository: https://gitlab.com/ecs-lab/exadata, including the spatial distribution of the nodes in the room.

Keywords

HPC, Supercomputing, Datacenter, High-performance computing

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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).
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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.
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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.
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