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ORCIDMichael E. Papka
Person information
- affiliation: University of Illinois Chicago, Department of Computer Science, Chicago, IL, USA
- affiliation: Argonne National Laboratory, Argonne, IL, USA
- affiliation (former): Northern Illinois University, Department of Computer Science, DeKalb, IL, USA
- affiliation (former, PhD 2009): University of Chicago, Chicago, IL, USA
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2020 – today
- 2025
[j50]Ratanond Koonchanok
, Michael E. Papka, Khairi Reda:
Trust Your Gut: Comparing Human and Machine Inference from Noisy Visualizations. IEEE Trans. Vis. Comput. Graph. 31(1): 754-764 (2025)- 2024
- [j49]Thomas Marrinan, Victor A. Mateevitsi, Madeleine Moeller, Alina Kanayinkal, Michael E. Papka:
2023 IEEE Scientific Visualization Contest Winner: VisAnywhere: Developing Multiplatform Scientific Visualization Applications. IEEE Computer Graphics and Applications 44(5): 93-103 (2024) - [c142]Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma:
A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. CCGrid 2024: 478-488 - [c141]Amey A. Salvi, Kecheng Lu, Michael E. Papka, Yunhai Wang, Khairi Reda:
Color Maker: a Mixed-Initiative Approach to Creating Accessible Color Maps. CHI 2024: 145:1-145:17 - [c140]Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka, Sanjif Shanmugavelu, Darshan Gandhi, Hengyu Zhao, Dun Ma, Kiran Ranganath, Rick Weisner, Jiunn-Yeu Chen, Yuting Yang, Natalia Vassilieva, Bin C. Zhang, Sylvia Howland, Alexander Tsyplikhin:
Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators. IPDPS (Workshops) 2024: 1-10 - [c139]Victor A. Mateevitsi, Andres Sewell, Mathis Bode, Paul F. Fischer, Jens Henrik Göbbert, Joseph A. Insley, Ioannis Kavroulakis, Damaskinos Konioris, Yu-Hsiang Lan, Misun Min, Dimitrios Papageorgiou, Michael E. Papka, Steve Petruzza, Silvio Rizzi, Ananias Tomboulides:
Visuals on the House: Optimizing HPC Workflows with No-Cost CPU Visualization. LDAV 2024: 69-70 - [c138]Colleen Heinemann, Jefferson Amstutz, Joseph A. Insley, Victor A. Mateevitsi, Michael E. Papka, Silvio Rizzi:
Graphical Representation Through a User Interface for In Situ Scientific Visualization with Ascent. LDAV 2024: 71-72 - [c137]Andres Sewell, Landon Dyken, Victor A. Mateevitsi, Will Usher, Jefferson Amstutz, Thomas Marrinan, Khairi Reda, Silvio Rizzi, Joseph A. Insley, Michael E. Papka, Sidharth Kumar, Steve Petruzza:
High-quality Approximation of Scientific Data using 3D Gaussian Splatting. LDAV 2024: 73-74 - [c136]Idunnuoluwa A. Adeniji, Joseph A. Insley, David A. Joiner, Victor A. Mateevitsi, Michael E. Papka, Silvio Rizzi:
Exploring Large-Scale Scientific Data in Virtual Reality. LDAV 2024: 75-76 - [c135]Gautham Dharuman, Kyle Hippe, Alexander Brace, Sam Foreman, Väinö Hatanpää, Varuni Katti Sastry, Huihuo Zheng, Logan T. Ward, Servesh Muralidharan, Archit Vasan, Bharat Kale, Carla M. Mann, Heng Ma, Yun-Hsuan Cheng, Yuliana Zamora, Shengchao Liu, Chaowei Xiao, Murali Emani, Tom Gibbs, Mahidhar Tatineni, Deepak Canchi, Jerome Mitchell, Koichi Yamada, Maria Garzaran, Michael E. Papka, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan:
MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization. SC 2024: 7 - [c134]Thomas Marrinan, Ethan Honzik, Hal L. N. Brynteson, Michael E. Papka:
Image Synthesis from a Collection of Depth Enhanced Panoramas: Creating Interactive Extended Reality Experiences from Static Images. IMX 2024: 64-74 - [c133]Victor A. Mateevitsi, Michael E. Papka, Khairi Reda:
Science in a Blink: Supporting Ensemble Perception in Scalar Fields. IEEE VIS 2024: 216-220 - [c132]Xiaolong Ma, Feng Yan, Lei Yang, Ian T. Foster, Michael E. Papka, Zhengchun Liu, Rajkumar Kettimuthu:
MalleTrain: Deep Neural Networks Training on Unfillable Supercomputer Nodes. ICPE 2024: 190-200 - [i23]Amey A. Salvi, Kecheng Lu, Michael E. Papka, Yunhai Wang, Khairi Reda:
Color Maker: a Mixed-Initiative Approach to Creating Accessible Color Maps. CoRR abs/2401.15032 (2024) - [i22]Boyang Li, Zhiling Lan, Michael E. Papka:
Interpretable Modeling of Deep Reinforcement Learning Driven Scheduling. CoRR abs/2403.16293 (2024) - [i21]Boyang Li, Yuping Fan, Matthew T. Dearing, Zhiling Lan, Paul Richy, William Allcocky, Michael E. Papka:
MRSch: Multi-Resource Scheduling for HPC. CoRR abs/2403.16298 (2024) - [i20]Xiaolong Ma, Feng Yan, Lei Yang, Ian T. Foster, Michael E. Papka, Zhengchun Liu, Rajkumar Kettimuthu:
MalleTrain: Deep Neural Network Training on Unfillable Supercomputer Nodes. CoRR abs/2404.15668 (2024) - [i19]Thomas Marrinan, Madeleine Moeller, Alina Kanayinkal, Victor A. Mateevitsi, Michael E. Papka:
VisAnywhere: Developing Multi-platform Scientific Visualization Applications. CoRR abs/2404.17619 (2024) - [i18]Victor A. Mateevitsi, Michael E. Papka, Khairi Reda:
Science in a Blink: Supporting Ensemble Perception in Scalar Fields. CoRR abs/2406.14452 (2024) - [i17]Ratanond Koonchanok, Michael E. Papka, Khairi Reda:
Trust Your Gut: Comparing Human and Machine Inference from Noisy Visualizations. CoRR abs/2407.16871 (2024) - 2023
- [j48]Bharat Kale, Austin Clyde, Maoyuan Sun, Arvind Ramanathan, Rick Stevens, Michael E. Papka:
ChemoGraph: Interactive Visual Exploration of the Chemical Space. Comput. Graph. Forum 42(3): 13-24 (2023) - [j47]Bharat Kale, Maoyuan Sun, Michael E. Papka:
The State of the Art in Visualizing Dynamic Multivariate Networks. Comput. Graph. Forum 42(3): 471-490 (2023) - [j46]Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan:
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37(6): 683-705 (2023) - [c131]Zhengchun Liu, Rajkumar Kettimuthu, Michael E. Papka, Ian T. Foster:
FreeTrain: A Framework to Utilize Unused Supercomputer Nodes for Training Neural Networks. CCGrid 2023: 299-310 - [c130]Boyang Li, Zhiling Lan, Michael E. Papka:
Interpretable Modeling of Deep Reinforcement Learning Driven Scheduling. MASCOTS 2023: 1-8 - [c129]Victor A. Mateevitsi, Mathis Bode, Nicola J. Ferrier, Paul F. Fischer, Jens Henrik Göbbert, Joseph A. Insley, Yu-Hsiang Lan, Misun Min, Michael E. Papka, Saumil Patel, Silvio Rizzi, Jonathan Windgassen:
Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI. SC Workshops 2023: 862-867 - [c128]Diego A. Roa Perdomo, Paige C. Kinsley, José Monsalve Diaz, Michael E. Papka, Xiaoming Li:
DEMAC: A Platform for Education in High-performance Computing, Bridging the Gap Between Users and Hardware. WCAE 2023 - [c127]Nickolaus D. Saint, Ryan Chard, Rafael Vescovi, Jim Pruyne, Ben Blaiszik, Rachana Ananthakrishnan, Michael E. Papka, Rick Wagner, Kyle Chard, Ian T. Foster:
Active Research Data Management with the Django Globus Portal Framework. PEARC 2023: 43-51 - [d1]Victor A. Mateevitsi, Mathis Bode, Nicola J. Ferrier, Paul F. Fischer, Jens Henrik Göbbert, Joseph A. Insley, Yu-Hsiang Lan, Misun Min, Michael E. Papka, Saumil Patel, Silvio Rizzi, Jonathan Windgassen:
Software and Analysis for paper: Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI. Zenodo, 2023
- [i16]Qi Wu, Joseph A. Insley, Victor A. Mateevitsi, Silvio Rizzi, Michael E. Papka, Kwan-Liu Ma:
Distributed Neural Representation for Reactive in situ Visualization. CoRR abs/2304.10516 (2023) - [i15]Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma:
A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. CoRR abs/2306.09457 (2023) - [i14]Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka:
A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators. CoRR abs/2310.04607 (2023) - [i13]Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens:
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - [i12]Victor A. Mateevitsi, Mathis Bode, Nicola J. Ferrier, Paul F. Fischer, Jens Henrik Göbbert, Joseph A. Insley, Yu-Hsiang Lan, Misun Min, Michael E. Papka, Saumil Patel, Silvio Rizzi, Jonathan Windgassen:
Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI. CoRR abs/2312.09888 (2023) - 2022
- [j45]Travis Mackoy, Bharat Kale, Michael E. Papka, Ralph A. Wheeler:
Corrigendum to "viewSq, a Visual Molecular Dynamics (VMD) module for calculating, analyzing, and visualizing X-ray and neutron structure factors from atomistic simulations" [Comput. Phys. Commun. 264 (2021) 107881]. Comput. Phys. Commun. 276: 108358 (2022) - [j44]Charlie Catlett, Pete Beckman, Nicola J. Ferrier, Michael E. Papka, Rajesh Sankaran, Jeff Solin, Valerie Taylor, Douglas Pancoast, Daniel A. Reed:
Hands-On Computer Science: The Array of Things Experimental Urban Instrument. Comput. Sci. Eng. 24(1): 57-63 (2022) - [j43]Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Ben Blaiszik, Jim Pruyne, Tekin Bicer, Alex Lavens, Zhengchun Liu, Michael E. Papka, Suresh Narayanan, Nicholas Schwarz, Kyle Chard, Ian T. Foster:
Linking scientific instruments and computation: Patterns, technologies, and experiences. Patterns 3(10): 100606 (2022) - [j42]Yuping Fan, Boyang Li, Dustin Favorite, Naunidh Singh, John Taylor Childers, Paul Rich, William E. Allcock, Michael E. Papka, Zhiling Lan:
DRAS: Deep Reinforcement Learning for Cluster Scheduling in High Performance Computing. IEEE Trans. Parallel Distributed Syst. 33(12): 4903-4917 (2022) - [c126]Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma:
Toward an In-Depth Analysis of Multifidelity High Performance Computing Systems. CCGRID 2022: 716-725 - [c125]Boyang Li, Yuping Fan, Matthew T. Dearing, Zhiling Lan, Paul Rich, William E. Allcock, Michael E. Papka:
MRSch: Multi-Resource Scheduling for HPC. CLUSTER 2022: 47-57 - [c124]Yuping Fan, Zhiling Lan, Paul Rich, William E. Allcock, Michael E. Papka:
Hybrid Workload Scheduling on HPC Systems. IPDPS 2022: 470-480 - [c123]Thomas Marrinan, Jifu Tan, Joseph A. Insley, Alina Kanayinkal, Michael E. Papka:
Interactive Virtual Reality Exploration of Large-Scale Datasets Using Omnidirectional Stereo Images. ISVC (1) 2022: 115-128 - [c122]Boyang Li, Yuping Fan, Michael E. Papka, Zhiling Lan:
Encoding for Reinforcement Learning Driven Scheduling. JSSPP 2022: 68-87 - [c121]Jason A. Ortiz, Joseph A. Insley, Janet Knowles, Victor A. Mateevitsi, Michael E. Papka, Silvio Rizzi:
Massive Data Visualization Techniques for use in Virtual Reality Devices. LDAV 2022: 1-2 - [c120]Nazariy Tishchenko, Nicola J. Ferrier, Joseph A. Insley, Victor A. Mateevitsi, Michael E. Papka, Silvio Rizzi, Jifu Tan:
Toward Bi-directional In Situ Visualization and Analysis of Blood Flow Simulations With Dynamic Deforming Walls. LDAV 2022: 1-2 - [c119]Murali Emani, Zhen Xie, Siddhisanket Raskar, Varuni Sastry, William Arnold, Bruce Wilson, Rajeev Thakur, Venkatram Vishwanath, Zhengchun Liu, Michael E. Papka, Cindy Orozco Bohorquez, Rick Weisner, Karen Li, Yongning Sheng, Yun Du, Jian Zhang, Alexander Tsyplikhin, Gurdaman Khaira, Jeremy Fowers, Ramakrishnan Sivakumar, Victoria Godsoe, Adrián Macías, Chetan Tekur, Matthew Boyd:
A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads. PMBS@SC 2022: 13-25 - [c118]Isaac Nealey, Nicola J. Ferrier, Joseph A. Insley, Victor A. Mateevitsi, Michael E. Papka, Silvio Rizzi:
Cinema Transfer: A Containerized Visualization Workflow. ISC Workshops 2022: 324-343 - [i11]Pratool Bharti, Priyanjani Chandra, Michael E. Papka, David Koop:
An Edge Map based Ensemble Solution to Detect Water Level in Stream. CoRR abs/2201.06098 (2022) - [i10]Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Ben Blaiszik, Jim Pruyne, Tekin Bicer, Alex Lavens, Zhengchun Liu, Michael E. Papka, Suresh Narayanan, Nicholas Schwarz, Kyle Chard, Ian T. Foster:
Linking Scientific Instruments and HPC: Patterns, Technologies, Experiences. CoRR abs/2204.05128 (2022) - 2021
- [j41]Khairi Reda, Amey A. Salvi, Jack Gray, Michael E. Papka:
Color Nameability Predicts Inference Accuracy in Spatial Visualizations. Comput. Graph. Forum 40(3): 49-60 (2021) - [j40]Travis Mackoy, Bharat Kale, Michael E. Papka, Ralph A. Wheeler:
viewSq, a Visual Molecular Dynamics (VMD) module for calculating, analyzing, and visualizing X-ray and neutron structure factors from atomistic simulations. Comput. Phys. Commun. 264: 107881 (2021) - [j39]Murali Emani, Venkatram Vishwanath, Corey Adams, Michael E. Papka, Rick Stevens, Laura Florescu, Sumti Jairath, William Liu, Tejas Nama, Arvind Sujeeth, Volodymyr V. Kindratenko, Anne C. Elster:
Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture. Comput. Sci. Eng. 23(2): 114-119 (2021) - [j38]Thomas Marrinan, Michael E. Papka:
Real-Time Omnidirectional Stereo Rendering: Generating 360° Surround-View Panoramic Images for Comfortable Immersive Viewing. IEEE Trans. Vis. Comput. Graph. 27(5): 2587-2596 (2021) - [c117]Yuping Fan, Zhiling Lan, J. Taylor Childers, Paul Rich, William E. Allcock, Michael E. Papka:
Deep Reinforcement Agent for Scheduling in HPC. IPDPS 2021: 807-816 - [c116]Bharat Kale, Maoyuan Sun, Michael E. Papka:
Direct Ordering: A Direct Manipulation Based Ordering Technique. IUI Workshops 2021 - [c115]Riley Lipinski, Kenneth Moreland, Michael E. Papka, Thomas Marrinan:
GPU-based Image Compression for Efficient Compositing in Distributed Rendering Applications. LDAV 2021: 43-52 - [c114]Anthony Bucaro, Connor Murphy, Nicola J. Ferrier, Joseph A. Insley, Victor A. Mateevitsi, Michael E. Papka, Silvio Rizzi, Jifu Tan:
Instrumenting Multiphysics Blood Flow Simulation Codes for In Situ Visualization and Analysis. LDAV 2021: 88-89 - [c113]Pambayun Savira, Thomas Marrinan, Michael E. Papka:
Writing, Running, and Analyzing Large-scale Scientific Simulations with Jupyter Notebooks. LDAV 2021: 90-91 - [i9]Yuping Fan, Zhiling Lan, J. Taylor Childers, Paul Rich, William E. Allcock, Michael E. Papka:
Deep Reinforcement Agent for Scheduling in HPC. CoRR abs/2102.06243 (2021) - [i8]Michael Salim, Thomas D. Uram, J. Taylor Childers, Venkat Vishwanath, Michael E. Papka:
Toward Real-time Analysis of Experimental Science Workloads on Geographically Distributed Supercomputers. CoRR abs/2105.06571 (2021) - [i7]Zhengchun Liu, Rajkumar Kettimuthu, Michael E. Papka, Ian T. Foster:
BFTrainer: Low-Cost Training of Neural Networks on Unfillable Supercomputer Nodes. CoRR abs/2106.12091 (2021) - [i6]Yuping Fan, Paul Rich, William E. Allcock, Michael E. Papka, Zhiling Lan:
Hybrid Workload Scheduling on HPC Systems. CoRR abs/2109.05412 (2021) - 2020
- [j37]Nils Heinonen, James J. Hack, Michael E. Papka:
Predicting the Risk of Cancer With Computational Electrodynamics. Comput. Sci. Eng. 22(1): 117-120 (2020) - [j36]James J. Hack, Michael E. Papka:
The U.S. High-Performance Computing Consortium in the Fight Against COVID-19. Comput. Sci. Eng. 22(6): 75-80 (2020) - [j35]Charlie Catlett, Peter H. Beckman, Nicola J. Ferrier, Howard C. Nusbaum, Michael E. Papka, Marc G. Berman, Rajesh Sankaran:
Measuring Cities with Software-Defined Sensors. J. Soc. Comput. 1(1): 14-27 (2020) - [c112]Zhengchun Liu, Ryan Lewis, Rajkumar Kettimuthu, Kevin Harms, Philip H. Carns, Nageswara S. V. Rao, Ian T. Foster, Michael E. Papka:
Characterization and identification of HPC applications at leadership computing facility. ICS 2020: 29:1-29:12 - [i5]Yuping Fan, Zhiling Lan, Paul Rich, William E. Allcock, Michael E. Papka, Brian Austin, David Paul:
Scheduling Beyond CPUs for HPC. CoRR abs/2012.05439 (2020)
2010 – 2019
- 2019
- [j34]Nils Heinonen, James J. Hack, Michael E. Papka:
Software Stack in a Snapshot. Comput. Sci. Eng. 21(3): 114-116 (2019) - [j33]Katie Elyce Jones, James J. Hack, Michael E. Papka:
Supercomputing Improves Predictions of Fluid Flow in Rock. Comput. Sci. Eng. 21(6): 74-76 (2019) - [j32]Thomas Marrinan, Greg Eisenhauer, Matthew Wolf, Joseph A. Insley, Silvio Rizzi, Michael E. Papka:
Parallel streaming between heterogeneous HPC resources for real-time analysis. J. Comput. Sci. 31: 163-171 (2019) - [c111]Sergei Shudler, Nicola J. Ferrier, Joseph A. Insley, Michael E. Papka, Saumil Patel, Silvio Rizzi:
Fast Mesh Validation in Combustion Simulations through In-Situ Visualization. EGPGV@EuroVis 2019: 7-16 - [c110]Yuping Fan, Zhiling Lan, Paul Rich, William E. Allcock, Michael E. Papka, Brian Austin, David Paul:
Scheduling Beyond CPUs for HPC. HPDC 2019: 97-108 - [c109]Thomas Marrinan, Silvio Rizzi, Joseph A. Insley, Lance Long, Luc Renambot, Michael E. Papka:
PxStream: Remote Visualization for Distributed Rendering Frameworks. LDAV 2019: 37-41 - [c108]Shilpika, Bethany Lusch, Murali Emani, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma:
MELA: A Visual Analytics Tool for Studying Multifidelity HPC System Logs. DAAC@SC 2019: 13-18 - [c107]Michael A. Salim, Thomas D. Uram, J. Taylor Childers, Venkatram Vishwanath, Michael E. Papka:
Balsam: Near Real-Time Experimental Data Analysis on Supercomputers. XLOOP@SC 2019: 26-31 - [c106]Sergei Shudler, Nicola J. Ferrier, Joseph A. Insley, Michael E. Papka, Silvio Rizzi:
Spack meets singularity: creating movable in-situ analysis stacks with ease. ISAV@SC 2019: 34-38 - [c105]Allen R. Sanderson, John A. Schmidt, Alan Humphrey, Michael E. Papka, Robert Sisneros:
In Situ Visualization of Performance Metrics in Multiple Domains. ProTools@SC 2019: 62-69 - [c104]Khairi Reda, Michael E. Papka:
Evaluating Gradient Perception in Color-Coded Scalar Fields. IEEE VIS (Short Papers) 2019: 271-275 - [c103]William E. Allcock, Benjamin S. Allen, Rachana Ananthakrishnan, Ben Blaiszik, Kyle Chard, Ryan Chard, Ian T. Foster, Lukasz Lacinski, Michael E. Papka, Rick Wagner:
Petrel: A Programmatically Accessible Research Data Service. PEARC 2019: 49:1-49:7 - [i4]Michael A. Salim, Thomas D. Uram, J. Taylor Childers, Prasanna Balaprakash, Venkatram Vishwanath, Michael E. Papka:
Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows. CoRR abs/1909.08704 (2019) - 2018
- [j31]Ryan Chard, Ravi K. Madduri, Nicholas T. Karonis, Kyle Chard, Kirk L. Duffin, Caesar E. Ordoñez, Thomas D. Uram, Justin Fleischauer, Ian T. Foster, Michael E. Papka, John Winans:
Scalable pCT Image Reconstruction Delivered as a Cloud Service. IEEE Trans. Cloud Comput. 6(1): 182-195 (2018) - [j30]Li Yu, Zhou Zhou, Yuping Fan, Michael E. Papka, Zhiling Lan:
System-wide trade-off modeling of performance, power, and resilience on petascale systems. J. Supercomput. 74(7): 3168-3192 (2018) - [c102]William E. Allcock, Bennett Bernardoni, Colleen Bertoni, Neil Getty, Joseph A. Insley, Michael E. Papka, Silvio Rizzi, Brian R. Toonen:
RAM as a Network Managed Resource. IPDPS Workshops 2018: 99-106 - [c101]Thomas Marrinan, Silvio Rizzi, Joseph A. Insley, Brian R. Toonen, William E. Allcock, Michael E. Papka:
Transferring Data from High-Performance Simulations to Extreme Scale Analysis Applications in Real-Time. IPDPS Workshops 2018: 1214-1220 - [c100]Joseph Adamo, J. D. Emberson, Edouard B. Brooks, Silvio Rizzi, Joseph A. Insley, Michael E. Papka:
Exploring Visualization Techniques with HACC Simulation Data. LDAV 2018: 92-93 - [c99]Bennett Bernardoni, Nicola J. Ferrier, Joseph A. Insley, Michael E. Papka, Saumil Patel, Silvio Rizzi:
In Situ Visualization and Analysis to Design Large Scale Experiments in Computational Fluid Dynamics. LDAV 2018: 94-95 - [c98]Preeti Malakar, Todd S. Munson, Christopher Knight, Venkatram Vishwanath, Michael E. Papka:
Topology-aware space-shared co-analysis of large-scale molecular dynamics simulations. SC 2018: 24:1-24:15 - [c97]Will Usher, Silvio Rizzi, Ingo Wald, Jefferson Amstutz, Joseph A. Insley, Venkatram Vishwanath, Nicola J. Ferrier, Michael E. Papka, Valerio Pascucci:
libIS: a lightweight library for flexible in transit visualization. ISAV@SC 2018: 33-38 - 2017
- [j29]John T. Childers, Thomas D. Uram, Thomas J. LeCompte, Michael E. Papka, D. P. Benjamin:
Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads. Comput. Phys. Commun. 210: 54-59 (2017) - [c96]Yuping Fan, Paul Rich, William E. Allcock, Michael E. Papka, Zhiling Lan:
Trade-Off Between Prediction Accuracy and Underestimation Rate in Job Runtime Estimates. CLUSTER 2017: 530-540 - [c95]Takanori Fujiwara, Preeti Malakar, Khairi Reda, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma:
A Visual Analytics System for Optimizing Communications in Massively Parallel Applications. VAST 2017: 59-70 - [c94]Sarah Read, Michael E. Papka:
Operational metrics reporting processes at scientific user facilities: Comparing a high-energy x-ray synchrotron facility to a supercomputing facility. ProComm 2017: 1-6 - [c93]Thomas Marrinan, Joseph A. Insley, Silvio Rizzi, Francois Tessier, Michael E. Papka:
Automated Dynamic Data Redistribution. IPDPS Workshops 2017: 1208-1215 - [c92]Christian Bailey, Bharat Kale, Jamieson Walker, Harish Varma Siravuri, Hamed Alhoori, Michael E. Papka:
Exploring Features for Predicting Policy Citations. JCDL 2017: 297-298 - [c91]Edouard B. Brooks, Joseph A. Insley, Michael E. Papka, Silvio Rizzi:
Virtual reality tools for the correction of automated volume segmentation errors using dense surface reconstructions. LDAV 2017: 92-93 - [c90]Preeti Malakar, Christopher Knight, Todd S. Munson, Venkatram Vishwanath, Michael E. Papka:
Scalable In situ Analysis of Molecular Dynamics Simulations. ISAV@SC 2017: 1-6 - [c89]Michael J. Lewis, George K. Thiruvathukal, Venkatram Vishwanath, Michael E. Papka, Andrew E. Johnson:
A distributed graph approach for pre-processing linked RDF data using supercomputers. SBD@SIGMOD 2017: 6:1-6:6 - [c88]Bharat Kale, Harish Varma Siravuri, Hamed Alhoori, Michael E. Papka:
Predicting Research that will be Cited in Policy Documents. WebSci 2017: 389-390 - [i3]Bharat Kale, Harish Varma Siravuri, Hamed Alhoori, Michael E. Papka:
Predicting Research that will be Cited in Policy Documents. CoRR abs/1706.04140 (2017) - [i2]Christian Bailey, Bharat Kale, Jamieson Walker, Harish Varma Siravuri, Hamed Alhoori, Michael E. Papka:
Exploring Features for Predicting Policy Citations. CoRR abs/1708.01658 (2017) - 2016
- [j28]Thomas D. Uram, Michael E. Papka:
Expanding the Scope of High-Performance Computing Facilities. Comput. Sci. Eng. 18(3): 84-87 (2016) - [j27]Khairi Reda, Andrew E. Johnson, Michael E. Papka, Jason Leigh:
Modeling and evaluating user behavior in exploratory visual analysis. Inf. Vis. 15(4): 325-339 (2016) - [j26]Huy Bui, Eun-Sung Jung, Venkatram Vishwanath, Andrew E. Johnson, Jason Leigh, Michael E. Papka:
Improving sparse data movement performance using multiple paths on the Blue Gene/Q supercomputer. Parallel Comput. 51: 3-16 (2016) - [j25]Paris Perdikaris, Joseph A. Insley, Leopold Grinberg, Yue Yu, Michael E. Papka, George E. Karniadakis:
Visualizing multiphysics, fluid-structure interaction phenomena in intracranial aneurysms. Parallel Comput. 55: 9-16 (2016) - [j24]Sean Wallace, Zhou Zhou, Venkatram Vishwanath, Susan Coghlan, John R. Tramm, Zhiling Lan, Michael E. Papka:
Application power profiling on IBM Blue Gene/Q. Parallel Comput. 57: 73-86 (2016) - [j23]Will Usher, Ingo Wald, Aaron Knoll, Michael E. Papka, Valerio Pascucci:
In Situ Exploration of Particle Simulations with CPU Ray Tracing. Supercomput. Front. Innov. 3(4): 4-18 (2016) - [j22]