Parallel Implementation of the Ensemble Empirical Mode Decomposition (PEEMD) and Its Application for Earth Science Data Analysis

To efficiently perform multiscale analysis of high-resolution, global, multiple-dimensional data sets, we have deployed the parallel ensemble empirical mode decomposition (PEEMD) package by implementing three-level parallelism into the ensemble Empirical Mode Decomposition (EMD), achieving a paralle...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Computing in science & engineering s. 1
Hlavní autoři: Shen, Bo-Wen, Cheung, Samson, Wu, Yu-ling, Li, Jui-Lin, Kao, David
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 08.06.2017
Témata:
and Visualization
Bridges
Computational modeling
Empirical mode decomposition
G Mathematics of Computing
G.4 Mathematical Software
G.4.a Algorithm design and analysis
G.4.e Parallel and vector implementations
Hurricanes
I Computing Methodologies
I.4 Image Processing and Computer Vision
I.4.10 Image Representation
I.4.10.c Multidimensional
I.6 Simulation
I.6.4 Model Validation and Analysis
I.6.8 Types of Simulation
I.6.8.h Parallel
Modeling
Object recognition
Parallel processing
ISSN:1521-9615
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract To efficiently perform multiscale analysis of high-resolution, global, multiple-dimensional data sets, we have deployed the parallel ensemble empirical mode decomposition (PEEMD) package by implementing three-level parallelism into the ensemble Empirical Mode Decomposition (EMD), achieving a parallel speedup of 720x using 200 eight-core processors. In this study, we discuss the implementation of the PEEMD and its application for the analysis of Earth science data, including the solution of Lorenz model, an idealized terrain-induced flow and real case Hurricane Sandy (2012), the latter of which is the second costliest hurricane in the US history.
AbstractList To efficiently perform multiscale analysis of high-resolution, global, multiple-dimensional data sets, we have deployed the parallel ensemble empirical mode decomposition (PEEMD) package by implementing three-level parallelism into the ensemble Empirical Mode Decomposition (EMD), achieving a parallel speedup of 720x using 200 eight-core processors. In this study, we discuss the implementation of the PEEMD and its application for the analysis of Earth science data, including the solution of Lorenz model, an idealized terrain-induced flow and real case Hurricane Sandy (2012), the latter of which is the second costliest hurricane in the US history.
Author Kao, David
Cheung, Samson
Wu, Yu-ling
Shen, Bo-Wen
Li, Jui-Lin
Author_xml – sequence: 1
  givenname: Bo-Wen
  surname: Shen
  fullname: Shen, Bo-Wen
– sequence: 2
  givenname: Samson
  surname: Cheung
  fullname: Cheung, Samson
– sequence: 3
  givenname: Yu-ling
  surname: Wu
  fullname: Wu, Yu-ling
– sequence: 4
  givenname: Jui-Lin
  surname: Li
  fullname: Li, Jui-Lin
– sequence: 5
  givenname: David
  surname: Kao
  fullname: Kao, David
BookMark eNo9kLFuwjAQhj1QqdD2AaouHtsBGieOk4wI0hYJVCTYo4tzFq4cO7KzsPXRmwDqdL903386fTMysc4iIc8sWjAWFe-71aFcxBHLFnGas4TxCZmyNGbzQrD0nsxC-ImiiOdFOiW_e_BgDBq6aTuDLdoeeu0sdYr2J6SlDdjWZghtp72WYOjONUjXKF3buaAv8Ou-LHfrNwq2oZs-0GXXmYG97JTztATfn-hBarRy6EIPdGnBnIMOj-ROgQn4dJsP5PhRHldf8-3352a13M6lGD-HDLJEKCVSzqXM0oKrXBRFLRQk2OQyjWUcqwKZQlHXDVd10kAtIAWV8JglD4Rdz0rvQvCoqs7rFvy5YlE1WqtGa9VorbpZGzov145GxH8-KzgfZCZ_7UBuXw
CODEN CSENFA
ContentType Journal Article
DBID 97E
RIA
RIE
AAYXX
CITATION
DOI 10.1109/MCSE.2017.2581314
DatabaseName IEEE Xplore (IEEE)
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Electronic Library (IEL)
CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Applied Sciences
Sciences (General)
EndPage 1
ExternalDocumentID 10_1109_MCSE_2017_2581314
7944521
Genre orig-research
GroupedDBID -~X
.DC
0R~
29F
4.4
5GY
6IK
6J9
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABQJQ
ABVLG
ACGFO
ACGFS
ACIWK
ADCTM
AENEX
AGKCL
AGQYO
AHBIQ
AHSDT
AKJIK
AKQYR
ALMA_UNASSIGNED_HOLDINGS
ATWAV
AZLTO
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
D0L
DU5
EBS
EJD
F5P
GX1
HZ~
IEDLZ
IFIPE
IPLJI
JAVBF
LAI
M43
O9-
OCL
P2P
PQQKQ
PZZ
RIA
RIE
TN5
TWZ
WH7
~02
5VS
AAYXX
AETIX
AGSQL
AI.
AIBXA
ALLEH
CITATION
H~9
IFJZH
MVM
RNI
ROL
RZB
VH1
ID FETCH-LOGICAL-c621-9a7a736ff6544cc7594f8699b6fa3ed8c52c22f9e1fe6bbd4fb3dab6a5af34213
IEDL.DBID RIE
ISSN 1521-9615
IngestDate Sat Nov 29 01:49:21 EST 2025
Tue Aug 26 16:34:41 EDT 2025
IsPeerReviewed true
IsScholarly true
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c621-9a7a736ff6544cc7594f8699b6fa3ed8c52c22f9e1fe6bbd4fb3dab6a5af34213
PageCount 1
ParticipantIDs crossref_primary_10_1109_MCSE_2017_2581314
ieee_primary_7944521
PublicationCentury 2000
PublicationDate 20170608
PublicationDateYYYYMMDD 2017-06-08
PublicationDate_xml – month: 6
  year: 2017
  text: 20170608
  day: 8
PublicationDecade 2010
PublicationTitle Computing in science & engineering
PublicationTitleAbbrev CISE-M
PublicationYear 2017
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0004895
Score 2.1079884
Snippet To efficiently perform multiscale analysis of high-resolution, global, multiple-dimensional data sets, we have deployed the parallel ensemble empirical mode...
SourceID crossref
ieee
SourceType Index Database
Publisher
StartPage 1
SubjectTerms and Visualization
Bridges
Computational modeling
Empirical mode decomposition
G Mathematics of Computing
G.4 Mathematical Software
G.4.a Algorithm design and analysis
G.4.e Parallel and vector implementations
Hurricanes
I Computing Methodologies
I.4 Image Processing and Computer Vision
I.4.10 Image Representation
I.4.10.c Multidimensional
I.6 Simulation
I.6.4 Model Validation and Analysis
I.6.8 Types of Simulation
I.6.8.h Parallel
Modeling
Object recognition
Parallel processing
Title Parallel Implementation of the Ensemble Empirical Mode Decomposition (PEEMD) and Its Application for Earth Science Data Analysis
URI https://ieeexplore.ieee.org/document/7944521
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVIEE
  databaseName: IEEE Electronic Library (IEL)
  issn: 1521-9615
  databaseCode: RIE
  dateStart: 19990101
  customDbUrl:
  isFulltext: true
  dateEnd: 99991231
  titleUrlDefault: https://ieeexplore.ieee.org/
  omitProxy: false
  ssIdentifier: ssj0004895
  providerName: IEEE
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T8MwELZKxcDCo4B46wYGigikedjxWNFUIAGqBANbdHZsgURT1LTM_HRs16EgsbCdrCQ65bvozvF99xFyaqWlQ84wEJqFQZLRJBCSp4EOKWqhzQJ1ROE79vCQPT_zUYtcfHNhlFKu-UxdWtOd5ZcTObe_yq5M7CSpZY2vMEYXXK0lBzJzCis2HQXcpGl_gmkcubq_fsxtExe7jNKsF_eSXznoh6iKyynDjf95s0nWfe0I_QXYW6Slqg7Z8HUk-K-07pCtxoQzP1W6u00-Rzi1uilv4AYCjz3nqIKJBlMEQl7VaizejDF-f3VzQ8DqpMFA2a5z39oFZ6M8vx90AasSbmc19Jfn32DKX8hNJL40rsAAZwjN2JMd8jTMn65vAi-_EEhqXyIyZDHV2sCZSMlSnuiMci6oxliVmUwjGUWaq55WVIgy0SIuUVBMUcdJ1It3SbuaVGqPAGJYShMRtj4wj-LCbIxjmaJAzMJU031y3uBRvC-GbBRucxLywoJXWPAKD94-2bZYfF_oYTj4e_mQrNmbXXNXdkTas-lcHZNV-TF7racnLoS-AOCoxSQ
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NT9wwEB0hQGovUKBV-Spz4ABVA9nEduIjYoNA7K5W6h64RWPHVpHYLNpdOPPTsb1eoFIvvY2syBrlTTTjeN48gGMvLZ3KghJlizRhpWCJ0pInNhVklXULIhCFe8VgUN7dyeEK_HrjwhhjQvOZOfNmuMtvJvrJ_yo7d7HDuGeNr3HGsnTB1npnQZZBY8UnpES6RB3vMJ0r5_3L35Vv4yrOMl528g77Kwt9kFUJWeVq8__8-QIbsXrEiwXcW7Bi2m3YjJUkxu90tg1bSxNP4lzp0x14GdLUK6c8YBgJPI6soxYnFl0ZiFU7M2P14Izx432YHIJeKQ27xvedx-YuPBlWVb97itQ2eDOf4cX7DTi6AhgrF4t_lq5gl-aEy8EnX2F0VY0ur5MowJBo4V8iFVTkwloHKNO64JLZUkiphKXcNKXmmc4yK03HGqFUw6zKG1KCONmcZZ38G6y2k9Z8ByRKG-1iwlcIbiup3NE415wUUZlyK3bh5xKP-nExZqMOx5NU1h682oNXR_B2Ycdj8fZghGHv38tH8Ol61O_VvZvB7T589huFVq_yAFbn0ydzCOv6eX4_m_4I4fQKStDIaw
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Parallel+Implementation+of+the+Ensemble+Empirical+Mode+Decomposition+%28PEEMD%29+and+Its+Application+for+Earth+Science+Data+Analysis&rft.jtitle=Computing+in+science+%26+engineering&rft.au=Shen%2C+Bo-Wen&rft.au=Cheung%2C+Samson&rft.au=Wu%2C+Yu-ling&rft.au=Li%2C+Jui-Lin&rft.date=2017-06-08&rft.issn=1521-9615&rft.spage=1&rft.epage=1&rft_id=info:doi/10.1109%2FMCSE.2017.2581314&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_MCSE_2017_2581314
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1521-9615&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1521-9615&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1521-9615&client=summon