TTK is Getting MPI-Ready

This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message Passing Interface (MPI). While several recent papers introduced topology-based approaches for distributed-memory environments, these were reporting...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on visualization and computer graphics Jg. 30; H. 8; S. 5875 - 5892
Hauptverfasser:	Le Guillou, Eve, Will, Michael, Guillou, Pierre, Lukasczyk, Jonas, Fortin, Pierre, Garth, Christoph, Tierny, Julien
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.08.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Schlagworte:	Algorithms Apexes Clustering algorithms Computer Science Data structures Distributed memory Distributed, Parallel, and Cluster Computing distributed-memory algorithms Documents high-performance computing Memory management Message passing Parallel processing Pipelines Preconditioning Software algorithms Software engineering Taxonomy Topological data analysis Topology Triangulation Distributed-memory algorithms High-performance computing HPC Pipelines Memory management Software algorithms Clustering algorithms Parallel processing Data structures Topology Topological data analysis
ISSN:	1077-2626, 1941-0506, 1941-0506
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message Passing Interface (MPI). While several recent papers introduced topology-based approaches for distributed-memory environments, these were reporting experiments obtained with tailored, mono-algorithm implementations. In contrast, we describe in this paper a versatile approach (supporting both triangulated domains and regular grids) for the support of topological analysis pipelines , i.e., a sequence of topological algorithms interacting together, possibly on distinct numbers of processes. While developing this extension, we faced several algorithmic and software engineering challenges, which we document in this paper. Specifically, we describe an MPI extension of TTK's data structure for triangulation representation and traversal, a central component to the global performance and generality of TTK's topological implementations. We also introduce an intermediate interface between TTK and MPI, both at the global pipeline level, and at the fine-grain algorithmic level. We provide a taxonomy for the distributed-memory topological algorithms supported by TTK, depending on their communication needs and provide examples of hybrid MPI+thread parallelizations. Detailed performance analyses show that parallel efficiencies range from 20% to 80% (depending on the algorithms), and that the MPI-specific preconditioning introduced by our framework induces a negligible computation time overhead. We illustrate the new distributed-memory capabilities of TTK with an example of advanced analysis pipeline, combining multiple algorithms, run on the largest publicly available dataset we have found (120 billion vertices) on a standard cluster with 64 nodes (for a total of 1536 cores). Finally, we provide a roadmap for the completion of TTK's MPI extension, along with generic recommendations for each algorithm communication category.
AbstractList	This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message Passing Interface (MPI). While several recent papers introduced topology-based approaches for distributed-memory environments, these were reporting experiments obtained with tailored, mono-algorithm implementations. In contrast, we describe in this paper a versatile approach (supporting both triangulated domains and regular grids) for the support of topological analysis pipelines , i.e., a sequence of topological algorithms interacting together, possibly on distinct numbers of processes. While developing this extension, we faced several algorithmic and software engineering challenges, which we document in this paper. Specifically, we describe an MPI extension of TTK's data structure for triangulation representation and traversal, a central component to the global performance and generality of TTK's topological implementations. We also introduce an intermediate interface between TTK and MPI, both at the global pipeline level, and at the fine-grain algorithmic level. We provide a taxonomy for the distributed-memory topological algorithms supported by TTK, depending on their communication needs and provide examples of hybrid MPI+thread parallelizations. Detailed performance analyses show that parallel efficiencies range from 20% to 80% (depending on the algorithms), and that the MPI-specific preconditioning introduced by our framework induces a negligible computation time overhead. We illustrate the new distributed-memory capabilities of TTK with an example of advanced analysis pipeline, combining multiple algorithms, run on the largest publicly available dataset we have found (120 billion vertices) on a standard cluster with 64 nodes (for a total of 1536 cores). Finally, we provide a roadmap for the completion of TTK's MPI extension, along with generic recommendations for each algorithm communication category. This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message Passing Interface (MPI). While several recent papers introduced topology-based approaches for distributed-memory environments, these were reporting experiments obtained with tailored, mono-algorithm implementations. In contrast, we describe in this paper a versatile approach (supporting both triangulated domains and regular grids) for the support of topological analysis pipelines, i.e., a sequence of topological algorithms interacting together, possibly on distinct numbers of processes. While developing this extension, we faced several algorithmic and software engineering challenges, which we document in this paper. Specifically, we describe an MPI extension of TTK's data structure for triangulation representation and traversal, a central component to the global performance and generality of TTK's topological implementations. We also introduce an intermediate interface between TTK and MPI, both at the global pipeline level, and at the fine-grain algorithmic level. We provide a taxonomy for the distributed-memory topological algorithms supported by TTK, depending on their communication needs and provide examples of hybrid MPI+thread parallelizations. Detailed performance analyses show that parallel efficiencies range from 20% to 80% (depending on the algorithms), and that the MPI-specific preconditioning introduced by our framework induces a negligible computation time overhead. We illustrate the new distributed-memory capabilities of TTK with an example of advanced analysis pipeline, combining multiple algorithms, run on the largest publicly available dataset we have found (120 billion vertices) on a standard cluster with 64 nodes (for a total of 1536 cores). Finally, we provide a roadmap for the completion of TTK's MPI extension, along with generic recommendations for each algorithm communication category.This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message Passing Interface (MPI). While several recent papers introduced topology-based approaches for distributed-memory environments, these were reporting experiments obtained with tailored, mono-algorithm implementations. In contrast, we describe in this paper a versatile approach (supporting both triangulated domains and regular grids) for the support of topological analysis pipelines, i.e., a sequence of topological algorithms interacting together, possibly on distinct numbers of processes. While developing this extension, we faced several algorithmic and software engineering challenges, which we document in this paper. Specifically, we describe an MPI extension of TTK's data structure for triangulation representation and traversal, a central component to the global performance and generality of TTK's topological implementations. We also introduce an intermediate interface between TTK and MPI, both at the global pipeline level, and at the fine-grain algorithmic level. We provide a taxonomy for the distributed-memory topological algorithms supported by TTK, depending on their communication needs and provide examples of hybrid MPI+thread parallelizations. Detailed performance analyses show that parallel efficiencies range from 20% to 80% (depending on the algorithms), and that the MPI-specific preconditioning introduced by our framework induces a negligible computation time overhead. We illustrate the new distributed-memory capabilities of TTK with an example of advanced analysis pipeline, combining multiple algorithms, run on the largest publicly available dataset we have found (120 billion vertices) on a standard cluster with 64 nodes (for a total of 1536 cores). Finally, we provide a roadmap for the completion of TTK's MPI extension, along with generic recommendations for each algorithm communication category. This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message Passing Interface (MPI). While several recent papers introduced topology-based approaches for distributed-memory environments, these were reporting experiments obtained with tailored, mono-algorithm implementations. In contrast, we describe in this paper a versatile approach (supporting both triangulated domains and regular grids) for the support of topological analysis pipelines, i.e. a sequence of topological algorithms interacting together. While developing this extension, we faced several algorithmic and software engineering challenges, which we document in this paper. We describe an MPI extension of TTK's data structure for triangulation representation and traversal, a central component to the global performance and generality of TTK's topological implementations. We also introduce an intermediate interface between TTK and MPI, both at the global pipeline level, and at the fine-grain algorithmic level. We provide a taxonomy for the distributed-memory topological algorithms supported by TTK, depending on their communication needs and provide examples of hybrid MPI+thread parallelizations. Performance analyses show that parallel efficiencies range from 20% to 80% (depending on the algorithms), and that the MPI-specific preconditioning introduced by our framework induces a negligible computation time overhead. We illustrate the new distributed-memory capabilities of TTK with an example of advanced analysis pipeline, combining multiple algorithms, run on the largest publicly available dataset we have found (120 billion vertices) on a cluster with 64 nodes (for a total of 1536 cores). Finally, we provide a roadmap for the completion of TTK's MPI extension, along with generic recommendations for each algorithm communication category.
Author	Fortin, Pierre Le Guillou, Eve Will, Michael Guillou, Pierre Lukasczyk, Jonas Garth, Christoph Tierny, Julien
Author_xml	– sequence: 1 givenname: Eve orcidid: 0009-0008-6123-2039 surname: Le Guillou fullname: Le Guillou, Eve email: eve.le_guillou@sorbonne-universite.fr organization: CNRS, Sorbonne Université and University of Lille, Paris, France – sequence: 2 givenname: Michael orcidid: 0009-0007-1344-3694 surname: Will fullname: Will, Michael email: mswill@rptu.de organization: RPTU Kaiserslautern-Landau, Kaiserslautern, Germany – sequence: 3 givenname: Pierre surname: Guillou fullname: Guillou, Pierre email: Pierre.Guillou@sorbonne-universite.fr organization: CNRS, Sorbonne Université, Paris, France – sequence: 4 givenname: Jonas orcidid: 0000-0001-6650-770X surname: Lukasczyk fullname: Lukasczyk, Jonas email: lukasczyk@rptu.de organization: RPTU Kaiserslautern-Landau, Kaiserslautern, Germany – sequence: 5 givenname: Pierre orcidid: 0000-0003-3117-9122 surname: Fortin fullname: Fortin, Pierre email: pierre.fortin@univ-lille.fr organization: Univ. Lille, CNRS, Centrale Lille, UMR 9189 CRIStAL, Lille, France – sequence: 6 givenname: Christoph orcidid: 0000-0003-1669-8549 surname: Garth fullname: Garth, Christoph email: garth@rptu.de organization: RPTU Kaiserslautern-Landau, Kaiserslautern, Germany – sequence: 7 givenname: Julien orcidid: 0000-0003-0056-2831 surname: Tierny fullname: Tierny, Julien email: Julien.Tierny@sorbonne-universite.fr organization: CNRS, Sorbonne Université, Paris, France
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/38630564$$D View this record in MEDLINE/PubMed https://hal.science/hal-04552256$$DView record in HAL
BookMark	eNpd0V1LwzAUBuAgih_TewWRgTd60XnOyUebyzF0EyeKVG9D2mZa2drZdIL_3oxOEa8SwvMmnLwHbLuqK8fYCcIAEfRV-jIaDwhIDDjXQKi32D5qgRFIUNthD3EckSK1xw68fwdAIRK9y_Z4ojhIJfbZcZre9UvfH7u2LavX_v3jbfTkbPF1yHZmdu7d0Wbtseeb63Q0iaYP49vRcBrlPNZthJQnSay4BQeZtkUMNiPMSAgsCHPOaaZnlKCMpXUZyoKcjZ1zmizkWeJ4j112977ZuVk25cI2X6a2pZkMp2Z9BkJKIqk-MdiLzi6b-mPlfGsWpc_dfG4rV6-84SCQOIVEoOf_6Hu9aqowSVCxFKSAU1BnG7XKFq74ff_nfwLADuRN7X3jZr8Ewaw7MOsOzLoDs-kgZE67TBnm_OMlCCU0_wYz73xV
CODEN	ITVGEA
Cites_doi	10.1109/TVCG.2023.3238008 10.1109/TVCG.2017.2743980 10.1109/LDAV57265.2022.9966403 10.1109/HiPC.2012.6507496 10.1109/TVCG.2010.253 10.1002/qua.26133 10.1109/TVCG.2011.249 10.1109/TVCG.2016.2599017 10.1109/TVCG.2015.2452919 10.1007/s00454-002-2885-2 10.1109/TVCG.2018.2864848 10.2307/1968813 10.1109/LDAV48142.2019.8944365 10.1111/cgf.12361 10.1137/1.9781611973198.4 10.1109/TVCG.2019.2948616 10.1109/VISUAL.2004.96 10.1109/TVCG.2023.3327182 10.1080/00029890.1970.11992523 10.1147/rd.45.0518 10.1109/TVCG.2006.186 10.1111/j.1365-2966.2011.18394.x 10.1007/978-3-319-04099-8_6 10.1007/978-3-030-43036-8_2 10.21105/joss.01370 10.1111/j.1467-8659.2012.03089.x 10.1109/TVCG.2020.3030353 10.1007/s00453-003-1052-3 10.1109/LDAV.2016.7874333 10.1109/TVCG.2015.2467432 10.1109/LDAV.2016.7874307 10.1016/b978-012387582-2/50038-1 10.1145/2442516.2442526 10.1109/TVCG.2014.2346403 10.1109/TVCG.2016.2570215 10.1109/TVCG.2023.3261981 10.1039/D2CP05893F 10.1109/TPAMI.2011.95 10.1109/TPDS.2019.2898436 10.1109/PACIFICVIS.2015.7156387 10.1002/jcc.25181 10.1007/978-3-030-83500-2_16 10.1109/TVCG.2012.228 10.1111/cgf.12933 10.1145/2814935 10.1090/mbk/069 10.1145/2535927 10.1145/3295500.3356188 10.1109/TVCG.2021.3076875 10.1109/TVCG.2008.119 10.1145/3447818.3460358 10.1016/j.jsc.2016.03.008 10.1109/LDAV57265.2022.9966394 10.1109/TVCG.2020.3030441
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024 licence_http://creativecommons.org/publicdomain/zero
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024 – notice: licence_http://creativecommons.org/publicdomain/zero
DBID	97E RIA RIE AAYXX CITATION NPM 7SC 7SP 8FD JQ2 L7M L~C L~D 7X8 1XC VOOES
DOI	10.1109/TVCG.2024.3390219
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef PubMed Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional MEDLINE - Academic Hyper Article en Ligne (HAL) Hyper Article en Ligne (HAL) (Open Access)
DatabaseTitle	CrossRef PubMed Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional MEDLINE - Academic
DatabaseTitleList	PubMed MEDLINE - Academic Technology Research Database
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher – sequence: 3 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Computer Science
EISSN	1941-0506
EndPage	5892
ExternalDocumentID	oai:HAL:hal-04552256v1 38630564 10_1109_TVCG_2024_3390219 10504649
Genre	orig-research Journal Article
GrantInformation_xml	– fundername: European Commission grantid: ERC-2019-COG funderid: 10.13039/501100000780
GroupedDBID	--- -~X .DC 0R~ 29I 4.4 53G 5GY 5VS 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACIWK AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD F5P HZ~ H~9 IEDLZ IFIPE IFJZH IPLJI JAVBF LAI M43 O9- OCL P2P PQQKQ RIA RIE RNI RNS RZB TN5 VH1 AAYXX CITATION NPM 7SC 7SP 8FD JQ2 L7M L~C L~D 7X8 1XC VOOES
ID	FETCH-LOGICAL-c379t-12c88763a0e0b9ad70ab21b2441d21c332f9f281575aeb15d2ea7eee92a0cb8e3
IEDL.DBID	RIE
ISICitedReferencesCount	3
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001262914400076&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1077-2626 1941-0506
IngestDate	Thu Nov 13 06:21:03 EST 2025 Sat Sep 27 19:43:03 EDT 2025 Sun Jun 29 16:52:31 EDT 2025 Mon Jul 21 06:01:36 EDT 2025 Sat Nov 29 03:31:48 EST 2025 Wed Aug 27 02:05:21 EDT 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	8
Keywords	Distributed-memory algorithms High-performance computing HPC Pipelines Memory management Software algorithms Clustering algorithms Parallel processing Data structures Topology Topological data analysis
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037 licence_http://creativecommons.org/publicdomain/zero/: http://creativecommons.org/publicdomain/zero
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c379t-12c88763a0e0b9ad70ab21b2441d21c332f9f281575aeb15d2ea7eee92a0cb8e3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ORCID	0000-0003-1669-8549 0000-0001-6650-770X 0009-0007-1344-3694 0009-0008-6123-2039 0000-0003-3117-9122 0000-0003-0056-2831
OpenAccessLink	https://hal.science/hal-04552256
PMID	38630564
PQID	3075426032
PQPubID	75741
PageCount	18
ParticipantIDs	ieee_primary_10504649 crossref_primary_10_1109_TVCG_2024_3390219 proquest_miscellaneous_3041232045 pubmed_primary_38630564 hal_primary_oai_HAL_hal_04552256v1 proquest_journals_3075426032
PublicationCentury	2000
PublicationDate	2024-08-01
PublicationDateYYYYMMDD	2024-08-01
PublicationDate_xml	– month: 08 year: 2024 text: 2024-08-01 day: 01
PublicationDecade	2020
PublicationPlace	United States
PublicationPlace_xml	– name: United States – name: New York
PublicationTitle	IEEE transactions on visualization and computer graphics
PublicationTitleAbbrev	TVCG
PublicationTitleAlternate	IEEE Trans Vis Comput Graph
PublicationYear	2024
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) – name: Institute of Electrical and Electronics Engineers
References	ref13 ref57 ref12 Edelsbrunner (ref16) 2004 ref56 ref15 ref59 ref14 Edwards (ref19) 2010 ref58 ref52 ref11 ref55 ref10 ref54 ref17 ref18 Gueunet (ref25) 2019 ref51 Forman (ref21) 2001; 48 ref46 ref45 ref48 ref47 ref42 Klacansky (ref36) 2020 ref41 ref49 (ref65) 2022 ref8 ref7 Favelier (ref20) 2016 ref9 ref4 ref3 ref6 ref5 (ref53) 2020 ref40 ref35 ref34 ref37 ref31 ref30 ref33 Tierny (ref62) 2017 ref32 ref2 ref1 ref39 ref38 (ref44) 2021 Maljovec (ref43) 2016 (ref64) 2020 ref24 ref23 ref67 ref26 ref63 ref22 ref66 ref28 ref27 ref29 Nigmetov (ref50) 2020 ref60 ref61
References_xml	– ident: ref26 doi: 10.1109/TVCG.2023.3238008 – ident: ref9 doi: 10.1109/TVCG.2017.2743980 – year: 2020 ident: ref64 article-title: TTK Data – volume: 48 volume-title: Sém. Lothar. Combin. year: 2001 ident: ref21 article-title: A user’s guide to discrete morse theory – year: 2020 ident: ref36 article-title: Open scientific visualization data sets – ident: ref48 doi: 10.1109/LDAV57265.2022.9966403 – ident: ref42 doi: 10.1109/HiPC.2012.6507496 – ident: ref10 doi: 10.1109/TVCG.2010.253 – ident: ref51 doi: 10.1002/qua.26133 – ident: ref35 doi: 10.1109/TVCG.2011.249 – ident: ref61 doi: 10.1109/TVCG.2016.2599017 – ident: ref57 doi: 10.1109/TVCG.2015.2452919 – ident: ref18 doi: 10.1007/s00454-002-2885-2 – ident: ref28 doi: 10.1109/TVCG.2018.2864848 – ident: ref30 doi: 10.2307/1968813 – ident: ref59 doi: 10.1109/LDAV48142.2019.8944365 – ident: ref27 doi: 10.1111/cgf.12361 – ident: ref5 doi: 10.1137/1.9781611973198.4 – ident: ref13 doi: 10.1109/TVCG.2019.2948616 – year: 2020 ident: ref50 article-title: Reeber: A. library for shared- and distributed-memory parallel computation of merge trees – year: 2021 ident: ref44 article-title: MPI: A message-passing interface standard, version 4.0 – ident: ref12 doi: 10.1109/VISUAL.2004.96 – ident: ref39 doi: 10.1109/TVCG.2023.3327182 – ident: ref4 doi: 10.1080/00029890.1970.11992523 – year: 2017 ident: ref62 article-title: The topology toolkit – ident: ref33 doi: 10.1147/rd.45.0518 – ident: ref38 doi: 10.1109/TVCG.2006.186 – ident: ref60 doi: 10.1111/j.1365-2966.2011.18394.x – ident: ref47 doi: 10.1007/978-3-319-04099-8_6 – ident: ref58 doi: 10.1007/978-3-030-43036-8_2 – year: 2022 ident: ref65 article-title: TTK online example database – ident: ref67 doi: 10.21105/joss.01370 – ident: ref56 doi: 10.1111/j.1467-8659.2012.03089.x – volume-title: Jacobi Sets of Multiple Morse Functions year: 2004 ident: ref16 – volume-title: Proc. IEEE SciVis Contest year: 2016 ident: ref20 article-title: Visualizing ensembles of viscous fingers – ident: ref40 doi: 10.1109/TVCG.2020.3030353 – ident: ref54 doi: 10.1007/s00453-003-1052-3 – ident: ref23 doi: 10.1109/LDAV.2016.7874333 – ident: ref29 doi: 10.1109/TVCG.2015.2467432 – ident: ref45 doi: 10.1109/LDAV.2016.7874307 – ident: ref2 doi: 10.1016/b978-012387582-2/50038-1 – ident: ref46 doi: 10.1145/2442516.2442526 – ident: ref22 doi: 10.1109/TVCG.2014.2346403 – ident: ref37 doi: 10.1109/TVCG.2016.2570215 – ident: ref41 doi: 10.1109/TVCG.2023.3261981 – ident: ref52 doi: 10.1039/D2CP05893F – ident: ref55 doi: 10.1109/TPAMI.2011.95 – ident: ref24 doi: 10.1109/TPDS.2019.2898436 – ident: ref1 doi: 10.1109/PACIFICVIS.2015.7156387 – ident: ref7 doi: 10.1002/jcc.25181 – ident: ref8 doi: 10.1007/978-3-030-83500-2_16 – ident: ref63 doi: 10.1109/TVCG.2012.228 – ident: ref31 doi: 10.1111/cgf.12933 – ident: ref34 doi: 10.1145/2814935 – ident: ref17 doi: 10.1090/mbk/069 – ident: ref14 doi: 10.1145/2535927 – year: 2020 ident: ref53 article-title: OpenMP application program interface version 5.1 – start-page: 27 volume-title: Proc. Eurographics Symp. Parallel Graph. Visual. year: 2019 ident: ref25 article-title: Task-based augmented Reeb graphs with dynamic ST-Trees – ident: ref49 doi: 10.1145/3295500.3356188 – ident: ref66 doi: 10.1109/TVCG.2021.3076875 – ident: ref3 doi: 10.1109/TVCG.2008.119 – ident: ref32 doi: 10.1145/3447818.3460358 – year: 2010 ident: ref19 article-title: SIERRA toolkit computational mesh conceptual model – ident: ref6 doi: 10.1016/j.jsc.2016.03.008 – ident: ref11 doi: 10.1109/LDAV57265.2022.9966394 – ident: ref15 doi: 10.1109/TVCG.2020.3030441 – start-page: 64 volume-title: Proc. IEEE Pacific Visual. Symp. year: 2016 ident: ref43 article-title: Topology-inspired partition-based sensitivity analysis and visualization of nuclear simulations
SSID	ssj0014489
Score	2.4644136
Snippet	This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message...
SourceID	hal proquest pubmed crossref ieee
SourceType	Open Access Repository Aggregation Database Index Database Publisher
StartPage	5875
SubjectTerms	Algorithms Apexes Clustering algorithms Computer Science Data structures Distributed memory Distributed, Parallel, and Cluster Computing distributed-memory algorithms Documents high-performance computing Memory management Message passing Parallel processing Pipelines Preconditioning Software algorithms Software engineering Taxonomy Topological data analysis Topology Triangulation
Title	TTK is Getting MPI-Ready
URI	https://ieeexplore.ieee.org/document/10504649 https://www.ncbi.nlm.nih.gov/pubmed/38630564 https://www.proquest.com/docview/3075426032 https://www.proquest.com/docview/3041232045 https://hal.science/hal-04552256
Volume	30
WOSCitedRecordID	wos001262914400076&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1941-0506 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0014489 issn: 1077-2626 databaseCode: RIE dateStart: 19950101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT8QgEJ64xhg9-H7UV6rxZFKlQBc4GuMrPuJhNXtrgLLRy65xd038987Q7kYPHrw1LQH6wTDfMMMAcOwFYx4VbVZo5dFA8Tqz1heZQLKsg5NCxq3sl3v1-Ki7XfPUHFaPZ2FCCDH4LJzSY_TlVwM_pq0ylPCCPHGmBS2lVH1Ya-oyQDvD1AGGKuNI0xsXZs7MWefl4hpNQS5PBZr4KKMLMC90m9iz_KWPWq8UDRmvWfmbcUbNc7X8zz6vwFJDMdPzek6swkzor8Hij8SD67Dd6dylb8P0OsSw5_Th6TajcPqvDXi-uuxc3GTNHQmZF8qMspx7TUnlLAvMGVspZh3PHSrtvOK5F4L3TI_rHFmZxWW5qHiwCjtpuGXe6SA2YbY_6IdtSCtpQk87pqVpS-e8qZzQuvKiCHklJU_gZIJU-V6nwiijCcFMSQiXhHDZIJzAEWI5LUdJrG_O70t6hyQSSV_R_swT2CDAftRWY5XA3gT7shGpYYmLUUHp9AV25HD6GYWBPBy2HwZjKiOJImILCWzVYzatfDLgO380ugsL9AN1cN8ezI4-xmEf5vzn6G34cYAzrqsP4oz7BmIvyo4
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NT9wwEB0VWhV6aGlLIRRKWvVUKeCvbOwjQsAilhWHFHGzbMcruOwidhep_54ZJ7uiBw7cosSynWeP541nPAb4HSRjARVtUeoqoIESdOFcKAuJZFlHr6RKW9nXg2o41Dc35qo7rJ7OwsQYU_BZPKDH5MtvJmFOW2Uo4SV54swKvC2VErw9rrV0GqClYdoQw6oQSNQ7JyZn5rC-Pj5DY1CoA4lGPkrpOryXukf8Wf2nkVZuKR4yXbTyMudMuuf00yt7vQEfO5KZH7Wz4jO8ieMv8OFZ6sGvsF3XF_ndND-LKfA5v7w6Lyig_t8m_D09qY_7RXdLQhFkZWYFF0FTWjnHIvPGNRVzXnCPaps3ggcpxciMhObIyxwuzGUjoquwk0Y4FryO8husjifjuA15o0wcac-0Mj3lfTCNl1o3QZaRNwh4Bn8WSNn7NhmGTUYEM5YQtoSw7RDO4BdiuSxHaaz7RwNL75BGIu0re488g00C7FltLVYZ7C6wt51QTS0uRyUl1JfYkZ_LzygO5ONw4ziZUxlFJBFbyGCrHbNl5YsB33mh0X1Y69eXAzs4H158h3X6mTbUbxdWZw_zuAfvwuPsbvrwI827J1UYzO0
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=TTK+is+Getting+MPI-Ready&rft.jtitle=IEEE+transactions+on+visualization+and+computer+graphics&rft.au=Le+Guillou%2C+Eve&rft.au=Will%2C+Michael&rft.au=Guillou%2C+Pierre&rft.au=Lukasczyk%2C+Jonas&rft.date=2024-08-01&rft.issn=1077-2626&rft.eissn=1941-0506&rft.volume=30&rft.issue=8&rft.spage=5875&rft.epage=5892&rft_id=info:doi/10.1109%2FTVCG.2024.3390219&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TVCG_2024_3390219
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1077-2626&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1077-2626&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1077-2626&client=summon