Evidence map›Paper›PMID 37202400›Full record

ArticleScientific data2023

M100 ExaData: a data collection campaign on the CINECA's Marconi100 Tier-0 supercomputer.

Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini and 2 more

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Andrea BorghesiAlma Mater Research Center for Human-Centered Artificial Intelligence, Bologna, 40121, Italy. andrea.borghesi3@unibo.it.ORCID 0000-0002-2298-2944
Carmine Di SantiUniversity of Bologna, DISI, Viale Risorgimento 2, Bologna, 40123, Italy.
Martin MolanUniversity of Bologna, DISI, Viale Risorgimento 2, Bologna, 40123, Italy.
Mohsen Seyedkazemi ArdebiliUniversity of Bologna, DISI, Viale Risorgimento 2, Bologna, 40123, Italy.
Alessio MauriCINECA, 40033 Casalecchio di Reno (BO), Casalecchio di Reno, Italy.
Massimiliano GuarrasiCINECA, 40033 Casalecchio di Reno (BO), Casalecchio di Reno, Italy.
Daniela GalettiCINECA, 40033 Casalecchio di Reno (BO), Casalecchio di Reno, Italy.
Mirko CestariCINECA, 40033 Casalecchio di Reno (BO), Casalecchio di Reno, Italy.
Francesco BarchiAlma Mater Research Center for Human-Centered Artificial Intelligence, Bologna, 40121, Italy. francesco.barchi@unibo.it.
Luca BeniniAlma Mater Research Center for Human-Centered Artificial Intelligence, Bologna, 40121, Italy.
Francesco BeneventiUniversity of Bologna, DISI, Viale Risorgimento 2, Bologna, 40123, Italy.
Andrea BartoliniAlma Mater Research Center for Human-Centered Artificial Intelligence, Bologna, 40121, Italy. a.bartolini@unibo.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Supercomputers are the most powerful computing machines available to society. They play a central role in economic, industrial, and societal development. While they are used by scientists, engineers, decision-makers, and data-analyst to computationally solve complex problems, supercomputers and their hosting datacenters are themselves complex power-hungry systems. Improving their efficiency, availability, and resiliency is vital and the subject of many research and engineering efforts. Still, a major roadblock hinders researchers: dearth of reliable data describing the behavior of production supercomputers. In this paper, we present the result of a ten-year-long project to design a monitoring framework (EXAMON) deployed at the Italian supercomputers at CINECA datacenter. We disclose the first holistic dataset of a tier-0 Top10 supercomputer. It includes the management, workload, facility, and infrastructure data of the Marconi100 supercomputer for two and half years of operation. The dataset (published via Zenodo) is the largest ever made public, with a size of 49.9TB before compression. We also provide open-source software modules to simplify access to the data and provide direct usage examples.

Identifiers

PMID37202400
PMCPMC10193329

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.