research-article

A terminology for in situ visualization and analysis systems

Authors: Hank Childs, Sean D. Ahern, James Ahrens, Andrew C. Bauer, Janine Bennett, E. Wes Bethel, Peer-Timo Bremer, Eric Brugger, Joseph Cottam, Matthieu Dorier, Soumya Dutta, Jean M. Favre, Thomas Fogal, Steffen Frey, Christoph Garth, Berk Geveci,

William F. Godoy, Charles D. Hansen, Cyrus Harrison, Bernd Hentschel, Joseph Insley, Chris R. Johnson, Scott Klasky, Aaron Knoll, James Kress, Matthew Larsen, Jay Lofstead, Kwan-Liu Ma, Preeti Malakar,

Jeremy Meredith, Kenneth Moreland, Paul Navrátil, Patrick O’Leary, Manish Parashar, Valerio Pascucci, John Patchett, Tom Peterka, Steve Petruzza, Norbert Podhorszki, David Pugmire, Michel Rasquin, Silvio Rizzi, David H. Rogers,

Sudhanshu Sane, Franz Sauer, Robert Sisneros, Han-Wei Shen, Will Usher, Rhonda Vickery, Venkatram Vishwanath, Ingo Wald, Ruonan Wang, Gunther H. Weber, Brad Whitlock, Matthew Wolf, Hongfeng Yu, Sean B. ZiegelerAuthors Info & Claims

The International Journal of High Performance Computing Applications, Volume 34, Issue 6

Pages 676 - 691

https://doi.org/10.1177/1094342020935991

Published: 01 November 2020 Publication History

Abstract

The term “in situ processing” has evolved over the last decade to mean both a specific strategy for visualizing and analyzing data and an umbrella term for a processing paradigm. The resulting confusion makes it difficult for visualization and analysis scientists to communicate with each other and with their stakeholders. To address this problem, a group of over 50 experts convened with the goal of standardizing terminology. This paper summarizes their findings and proposes a new terminology for describing in situ systems. An important finding from this group was that in situ systems are best described via multiple, distinct axes: integration type, proximity, access, division of execution, operation controls, and output type. This paper discusses these axes, evaluates existing systems within the axes, and explores how currently used terms relate to the axes.

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Author biographies

Hank Childs is an Associate Professor of Computer and Information Science at the University of Oregon. He received his Ph.D. from the University of California at Davis in 2006. His research interests include in situ processing, scientific visualization systems, and data reduction.

Sean D. Ahern is a Lead Software Developer at Ansys in the Physics Business Unit. He received dual Bachelor’s Degrees of Science in Computer Science and Mathematics (Honors) from Purdue University. His research interests include scientific visualization architectures, high-performance computing, and scalable rendering.

James Ahrens is Senior Scientist in the Data Science at Scale team at Los Alamos National Laboratory. He received his Ph.D. in Computer Science from the University of Washington in 1996. His research interests include data science, scientific visualization, data management and high-performance computing.

Andrew C. Bauer is a Research Mechanical Engineer at the Data Analysis and Assessment Center which is a component of the United States Department of Defense’s High Performance Computing Modernization Program. He received his Ph.D. from the University at Buffalo in 2003. His research interests include in situ analysis, scientific visualization and scientific workflows.

Janine C. Bennett is manager of the Extreme-Scale Data Science & Analytics Department at Sandia National Laboratories. She received her Ph.D. from the University of California at Davis in 2008. Her research interests include in situ analysis, data reduction, and programming models research.

E. Wes Bethel is a Senior Computer Scientist at Lawrence Berkeley National Laboratory. His Ph.D. from University of California at Davis is in Computer Science, and his research interests include software architecture, high performance computing, scientific and information visualization, computer graphics, computer vision, image analysis, data science, and machine learning.

Peer-Timo Bremer is a Computer Scientist at Lawrence Livermore National Laboratory and the Associate Director for Research at the Center for Extreme Data Management Analysis and Visualization at the University of Utah. He received his Ph.D. in Computer Science in 2004 from the University of California, Davis. His research spans large scale data analysis and visualization, topological techniques, and scientific machine learning.

Eric Brugger is a Computer Scientist at the Lawrence Livermore National Laboratory. He received his B.S. from the University of California at Berkeley in 1985. His research interests include in situ processing, scientific visualization, and high performance computing.

Joseph Cottam is a research scientist at Pacific Northwest National Laboratory. He received his Ph.D. from Indiana University in 2011. His research interests include visual analytics, programming language design and graph analysis.

Matthieu Dorier is a software development specialist in the Mathematics and Computer Science division of Argonne National Laboratory. He received his Ph.D. from Ecole Normale Supérieure de Rennes, France, in 2014. His research interests include I/O and data storage, HPC data services, and in situ analysis.

Soumya Dutta is a staff scientist in the Data Science at Scale team at Los Alamos National Laboratory. He received his Ph.D. in Computer Science and Engineering from the Ohio State University in 2018. His research interests include in situ data analysis, visualization, data reduction, HPC, multivariate and time-varying data analysis, and uncertainty visualization.

Jean M. Favre is a Senior Visualization Software Engineer at the Swiss National Supercomputing Center. He received his Ph.D. from The George Washington University in Washington DC, in 1995. His research interests include high performance computing, in situ visualization and analysis, parallel I/O and visualization, and computer graphics.

Thomas Fogal is a software developer at Apple, where he applies his early background in large data processing to compiling machine learning models. His research interests are in high-performance software.

Steffen Frey is a PostDoc at the University of Stuttgart Visualization Research Center. He received his Ph.D. degree in computer science from the same institution. His research interests include visualization for large and complex scientific data, focusing on performance-related aspects, parameter tradeoffs and optimization, as well as representations of dynamic processes.

Christoph Garth is a Full Professor at Technische Universität Kaiserslautern, Germany, in the Computer Science department. He received his Ph.D. from Technische Universität Kaiserslautern in 2007. His research interests include visualization of complex, large-scale dataset, high-performance algorithms for visualization, topological analysis in visualization, and analytics interfaces for scientific datasets.

Berk Geveci leads the scientific computing team at Kitware Inc. He received his Ph.D. from Lehigh University in 1999. His research interests include in situ data analysis and visualization and scientific visualization.

William F. Godoy is a Research Scientist at Oak Ridge National Laboratory. A member of IEEE and ASME societies, he received his Ph.D. from SUNY Buffalo in Mechanical Engineering in 2009. His research interests include high performance computing, computational physics, parallel I/O, and software engineering.

Charles D. Hansen is a Distinguished Professor at the University of Utah in the School of Computing and Scientific Computing and Imaging (SCI) Institute and an IEEE Fellow. He received his Ph.D. from the University of Utah in 1987. His research has made contributions to the fields of scientific visualization, computer graphics, parallel computation and computer vision.

Cyrus Harrison is a Computer Scientist and Associate Division Leader at Lawrence Livermore National Laboratory. He received his Masters of Engineering in Computer Engineering in 2004 from University of Florida. His research interests include scientific visualization, data analysis, and in situ processing.

Bernd Hentschel is a data scientist with d.velop AG operating out of Gescher, Germany. He received a Ph.D. in computer science from RWTH Aachen University in 2009. His research interests include data visualization at large with a focus on parallel particle advection and feature tracking algorithms.

Joseph Insley is the Team Lead for Visualization and Data Analysis at the Argonne Leadership Computing Facility. He received his M.S. in Computer Science in 2002, and M.F.A. in 1997, both from the University of Illinois at Chicago. His research interests include the development of parallel and scalable methods for large-scale data analysis and visualization and in situ workflows on current and next-generation systems.

Chris R. Johnson is a Distinguished Professor at the University of Utah in the School of Computing and Scientific Computing and Imaging (SCI) Institute. He received his Ph.D. from the University of Utah in 1989. His research interests include visualization, image analysis, and scientific computing.

Scott Klasky is a distinguished scientist at Oak Ridge National Laboratory. He received his Ph.D. from the University of Texas at Austin. His research interests include scientific computing and data management.

Aaron Knoll is a Senior Graphics Engineer at Intel Corporation. He received is Ph.D. from the University of Utah in 2009. His interests include ray tracing, volume rendering and large scale scientific visualization.

James Kress is a Computer Scientist at Oak Ridge National Laboratory. He received his Ph.D. from the University of Oregon in Computer and Information Science. His research interests include high performance computing, scientific visualization, in situ visualization and analysis, and performance modeling.

Matthew Larsen is a staff scientist at Lawrence Livermore National Laboratory. He received his Ph.D. from the University of Oregon in Computer and Information Science. His research interests include rendering, scientific visualization, in situ analysis, and high performance computing.

Jay Lofstead is a Principal Member of Technical Staff at Sandia National Laboratories. He received his Ph.D. in Computer Science from Georgia Tech in 2010. His research interests include data management, workflows, IO, storage, reproducibility, and software engineering.

Kwan-Liu Ma is a Distinguished Professor of Computer Science at the University of California at Davis. He received his Ph.D. from the University of Utah in 1993. HIs research interests include visualization, computer graphics, human computer interaction, and high performance computing.

Preeti Malakar is an Assistant Professor of Computer Science at the Indian Institute of Technology Kanpur. She received her Ph.D. from the Indian Institute of Science Bangalore in 2014. Her research interests include high performance computing, scientific workflow optimization, parallel I/O and performance analysis of parallel codes.

Jeremy Meredith was a staff scientist at Oak Ridge National Laboratory during the writing of this article. He now works at Google. He received his M.S. in Computer Science from Stanford.

Kenneth Moreland is a Principal Member of Technical Staff at Sandia National Laboratories. He received his Ph.D. from the University of New Mexico in 2004. His current interests include the design and development of visualization algorithms and systems to run on multi-core, many-core, and future-generation computer hardware.

Paul Navrátil is a Research Scientist and Director of Visualization at the Texas Advanced Computing Center at the University of Texas at Austin. He received his Ph.D. in Computer Science from the University of Texas at Austin in 2010. His research interests include large-scale parallel visualization, large-scale local and remote visualization systems, and local and remote human-data interaction methodologies.

Patrick O’Leary is an assistant director of scientific computing at Kitware, Inc. He received his Ph.D. from the University of Wyoming in 1999. His research interests include high-performance computing (HPC), Cloud/Web computing, numerical analysis, and in situ analysis and visualization.

Manish Parashar is Distinguished Professor of Computer Science at Rutgers University and founding Director of the Rutgers Discovery Informatics Institute (RDI²). He received his Ph.D. from Syracuse University in 1994. His research interests are in the broad areas of Parallel and Distributed Computing and Computational and Data-Enabled Science and Engineering.

Valerio Pascucci is the John R. Parks Inaugural Endowed Chair of Computer Science at the University of Utah and founding Director of the Center for Extreme Data Management Analysis and Visualization (CEDMAV). He received his Ph.D. in Computer Science from Purdue University in 2000. His research interests include large scale scientific visualization, HPC, in situ analytics, topology, data streaming, and file formats.

John Patchett is the Production Visualization Project Lead and the Deputy Team Leader of the Data Science at Scale team at the Los Alamos National Laboratory. He received his Doctor of Engineering from the Technical University of Kaiserslautern in 2017. His research interests primarily focus on issues surrounding large-scale, parallel, distributed memory visualization and data analysis of simulation data.

Tom Peterka is a computer scientist at Argonne National Laboratory, scientist at the University of Chicago Consortium for Advanced Science and Engineering (CASE), and fellow of the Northwestern Argonne Institute for Science and Engineering (NAISE). Peterka received his Ph.D. in computer science from the University of Illinois at Chicago in 2007. His research interests are in large-scale parallel in situ analysis of scientific data.

Steve Petruzza is a Research Associate at the Scientific Computing and Imaging Institute at the University of Utah. He received his Ph.D. from the University of Rome “Tor Vergata”, Italy. His research interests include high performance computing, in situ analysis and scientific visualization.

Norbert Podhorszki is Senior Research Staff at the Computer Science and Mathematics Division of the Oak Ridge National Laboratory. He received his Ph.D. from Eötvös Loránd University, Budapest, Hungary in 2005. His research interest include high performance I/O, code coupling, in situ data processing and workflow automation

David Pugmire is a Senior Research Scientist at the Oak Ridge National Laboratory. He received his Ph.D. from the University of Utah in 2000. His research interests include high performance computing, scientific visualization, in situ visualization and analysis.

Michel Rasquin is a Senior Research Engineer at Cenaero. He received his Ph.D. from the University of Brussels and from the von Karman Institute for Fluid Dynamics. His research interests include high-fidelity CFD simulations of complex flows, high performance computing and data visualization.

Silvio Rizzi is an Assistant Computer Scientist at Argonne National Laboratory. He received his PhD from the University of Illinois-Chicago. His research interests include large-scale scientific visualization, computer graphics, and in situ visualization and analysis.

David H. Rogers is Team Lead and Senior Scientist of the Data Science at Scale team at Los Alamos National Laboratory. He received his M.S. in Computer Science from the University of New Mexico. His research interests include in situ, high dimensional and assisted data analysis and visualization.

Sudhanshu Sane is a computer and information science Ph.D. candidate at the University of Oregon. He received his masters from the University of Oregon in 2016. His research interests include in situ processing, flow visualization, and data reduction.

Franz Sauer is a software engineer at Walt Disney Animation Studios. He received his Ph.D. from the University of California at Davis in 2017. His research interests include computer graphics, physics-based simulations, and data visualization.

Robert Sisneros is a Senior Research Scientist and leader of the Data Analysis and Visualization team at the National Center for Supercomputing Applications. He received his Ph.D. from the University of Tennessee at Knoxville in 2009. His research interests include data models and representations, parallel analysis algorithms, I/O parameter optimization, and ‘big data’ analytics.

Han-Wei Shen is a full professor at The Ohio State University. He received his PhD degree in computer science from the University of Utah in 1998. His primary research interests are scientific visualization, machine learning, artificial intelligence, and computer graphics.

Will Usher is a Graduate Research Assistant at the Scientific Computing and Imaging Institute at the University of Utah. He is currently pursuing his Ph.D. in Computer Science under Valerio Pascucci at the University of Utah. His research interests include distributed rendering, virtual reality, in situ visualization and ray tracing.

Rhonda Vickery is a research scientist at Wright State University. She received her Ph.D. from Mississippi State University in 2003. Her research interests include high performance data analytics, visual analysis, and efficient data management.

Venkatram Vishwanath is a Computer Scientist at Argonne National Laboratory. He received his Ph.D. in Computer Science from the University of Illinois at Chicago in 2009. His research interests include supercomputing architectures, parallel algorithms and runtimes, scalable analytics and collaborative workspaces.

Ingo Wald is a Director, Ray Tracing, at NVIDIA. He received his Ph.D. (Dr.-ing.) in Computer Science from Saarland University. His research interests include everything and anything that involves ray tracing, with a focus of applying ray tracing to solve challenging visualization problems.

Ruonan Wang is a software engineer at the Oak Ridge National Laboratory. He received his Ph.D. from the University of Western Australia in 2017. His research interests include data I/O middleware design and data staging.

Gunther H. Weber is a Staff Scientist at Lawrence Berkeley National Laboratory and an Adjunct Associate Professor of Computer Science at the University of California, Davis. He received his Ph.D. from Technische Universität Kaiserslautern in 2003. His research interests include data analysis and visualization, parallel and distributed computing, in situ processing and topological data analysis.

Brad Whitlock is a Senior Visualization Engineer at Intelligent Light. He received a Bachelor of Science in Computer Science from California State University, Sacramento, in 1998. His research interests include in situ scientific visualization, parallel programming, and computer graphics.

Matthew Wolf is a Senior Computer Scientist at Oak Ridge National Laboratory. He received his Ph.D. from the Georgia Institute of Technology in 2000. His research interests include high performance and scalable computing, in situ runtime systems, and I/O and adaptive event middleware.

Hongfeng Yu is an Associate Professor of Computer Science and Engineering at the University of Nebraska-Lincoln. He received his Ph.D. from the University of California at Davis in 2008. His research interests include large-scale data analysis and visualization, high-performance computing, and user interfaces and interaction.

Sean B. Ziegeler is a Computational Scientist at General Dynamics Information Technology for the DoD High Performance Computing Modernization Program. He received his Ph.D. from Mississippi State University in 2012. His research interests include high performance computing, scientific visualization and analysis, data reduction, and parallel I/O.

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Index Terms

A terminology for in situ visualization and analysis systems
1. Computing methodologies
2. Human-centered computing
  1. Human computer interaction (HCI)

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cover image International Journal of High Performance Computing Applications

International Journal of High Performance Computing Applications Volume 34, Issue 6

Nov 2020

104 pages

ISSN:1094-3420

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Sage Publications, Inc.

United States

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Published: 01 November 2020

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Tahir RNonaka JIwata KMatsushima TSakamoto NBi CNakao MMurai H(2024)Analysis Towards Energy-Aware Image-based In Situ Visualization on the FugakuProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3635035.3635048(154-163)Online publication date: 18-Jan-2024
https://dl.acm.org/doi/10.1145/3635035.3635048
Hegde DMalakar P(2023)Accelerating In Situ Analysis using Non-volatile MemoryProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624176(995-1004)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624176
Meyer FHernandez BPausch RWidera RGroß DBastrakov SHuebl AJuckeland GKelling JLeinhauser MRogers DSchramm USteiniger KGumhold SYoung JBussmann MChandrasekaran SDebus AHuebl ASilvano CRobinson T(2023)Hardware-Agnostic Interactive Exascale In Situ Visualization of Particle-In-Cell SimulationsProceedings of the Platform for Advanced Scientific Computing Conference10.1145/3592979.3593408(1-14)Online publication date: 26-Jun-2023
https://dl.acm.org/doi/10.1145/3592979.3593408
Bruder VLarsen MErtl TChilds HFrey S(2023)A Hybrid in Situ Approach for Cost Efficient Image Database GenerationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.316959029:9(3788-3798)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1109/TVCG.2022.3169590
Dorier MWang ZRamesh SAyachit USnyder SRoss RParashar M(2023)Towards elastic in situ analysis for high-performance computing simulationsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2023.02.014177:C(106-116)Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1016/j.jpdc.2023.02.014
Vasev P(2023)A Computational Model for Interactive Visualization of High-Performance ComputationsSupercomputing10.1007/978-3-031-49435-2_9(118-133)Online publication date: 25-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-49435-2_9
Kress JHolst GDasari HAfzal SHoteit ITheußl T(2023)Inshimtu – A Lightweight In Situ Visualization “Shim”High Performance Computing10.1007/978-3-031-40843-4_19(257-268)Online publication date: 21-May-2023
https://dl.acm.org/doi/10.1007/978-3-031-40843-4_19
Li FSong F(2023)INSTANT: A Runtime Framework to Orchestrate In-Situ WorkflowsEuro-Par 2023: Parallel Processing10.1007/978-3-031-39698-4_14(199-213)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1007/978-3-031-39698-4_14
Gainaru AWan LWang RSuchyta EChen JPodhorszki NKress JPugmire DKlasky S(2022)Understanding the Impact of Data Staging for Coupled Scientific WorkflowsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2022.317998933:12(4134-4147)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1109/TPDS.2022.3179989
Pugmire DHuang JMoreland KKlasky S(2022)The Need for Pervasive In Situ Analysis and Visualization (P-ISAV)High Performance Computing. ISC High Performance 2022 International Workshops10.1007/978-3-031-23220-6_21(306-316)Online publication date: 29-May-2022
https://dl.acm.org/doi/10.1007/978-3-031-23220-6_21
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Loosely Coupled In Situ Visualization: A Perspective on Why It's Here to Stay

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Hardware-Agnostic Interactive Exascale In Situ Visualization of Particle-In-Cell Simulations

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