↓ Skip to main content

High Performance Computing

Overview of attention for book
Cover of 'High Performance Computing'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Compiler-Assisted Type-Safe Checkpointing
  3. Altmetric Badge
    Chapter 2 Static Analysis to Enhance Programmability and Performance in OmpSs-2
  4. Altmetric Badge
    Chapter 3 Automatic Detection of MPI Assertions
  5. Altmetric Badge
    Chapter 4 Automatic Code Motion to Extend MPI Nonblocking Overlap Window
  6. Altmetric Badge
    Chapter 5 Complete Deep Computer-Vision Methodology for Investigating Hydrodynamic Instabilities
  7. Altmetric Badge
    Chapter 6 Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning
  8. Altmetric Badge
    Chapter 7 Unsupervised Learning of Particle Image Velocimetry
  9. Altmetric Badge
    Chapter 8 Reduced Order Modeling of Dynamical Systems Using Artificial Neural Networks Applied to Water Circulation
  10. Altmetric Badge
    Chapter 9 Parameter Identification of RANS Turbulence Model Using Physics-Embedded Neural Network
  11. Altmetric Badge
    Chapter 10 Investigating the Overhead of the REST Protocol When Using Cloud Services for HPC Storage
  12. Altmetric Badge
    Chapter 11 Characterizing I/O Optimization Effect Through Holistic Log Data Analysis of Parallel File Systems and Interconnects
  13. Altmetric Badge
    Chapter 12 The Importance of Temporal Behavior When Classifying Job IO Patterns Using Machine Learning Techniques
  14. Altmetric Badge
    Chapter 13 GOPHER, an HPC Framework for Large Scale Graph Exploration and Inference
  15. Altmetric Badge
    Chapter 14 Ensembles of Networks Produced from Neural Architecture Search
  16. Altmetric Badge
    Chapter 15 SmartPred: Unsupervised Hard Disk Failure Detection
  17. Altmetric Badge
    Chapter 16 Application IO Analysis with Lustre Monitoring Using LASSi for ARCHER
  18. Altmetric Badge
    Chapter 17 AI-Driven Holistic Approach to Energy Efficient HPC
  19. Altmetric Badge
    Chapter 18 Characterizing HPC Performance Variation with Monitoring and Unsupervised Learning
  20. Altmetric Badge
    Chapter 19 Service Function Chaining Based on Segment Routing Using P4 and SR-IOV (P4-SFC)
  21. Altmetric Badge
    Chapter 20 Seamlessly Managing HPC Workloads Through Kubernetes
  22. Altmetric Badge
    Chapter 21 Interference-Aware Orchestration in Kubernetes
  23. Altmetric Badge
    Chapter 22 RustyHermit: A Scalable, Rust-Based Virtual Execution Environment
  24. Altmetric Badge
    Chapter 23 Rootless Containers with Podman for HPC
  25. Altmetric Badge
    Chapter 24 Bioinformatics Application with Kubeflow for Batch Processing in Clouds
  26. Altmetric Badge
    Chapter 25 Converging HPC, Big Data and Cloud Technologies for Precision Agriculture Data Analytics on Supercomputers
Attention for Chapter 8: Reduced Order Modeling of Dynamical Systems Using Artificial Neural Networks Applied to Water Circulation
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

2 X users


5 Dimensions

Readers on

6 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Reduced Order Modeling of Dynamical Systems Using Artificial Neural Networks Applied to Water Circulation
Chapter number 8
Book title
High Performance Computing
Published in
arXiv, October 2020
DOI 10.1007/978-3-030-59851-8_8
Book ISBNs
978-3-03-059850-1, 978-3-03-059851-8

Alberto Costa Nogueira, João Lucas de Sousa Almeida, Guillaume Auger, Campbell D. Watson, Alberto Costa Nogueira Jr, Costa Nogueira, Alberto, de Sousa Almeida, João Lucas, Auger, Guillaume, Watson, Campbell D.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 17%
Student > Ph. D. Student 1 17%
Student > Bachelor 1 17%
Other 1 17%
Student > Master 1 17%
Other 0 0%
Unknown 1 17%
Readers by discipline Count As %
Computer Science 2 33%
Unspecified 1 17%
Mathematics 1 17%
Energy 1 17%
Unknown 1 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 March 2021.
All research outputs
of 23,253,955 outputs
Outputs from arXiv
of 958,527 outputs
Outputs of similar age
of 419,536 outputs
Outputs of similar age from arXiv
of 34,673 outputs
Altmetric has tracked 23,253,955 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 958,527 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 419,536 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34,673 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.