Katherine E. Isaacs

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Project Code

Conference, Journal, & Workshop Publications

K. Williams, A. Bigelow, and K. E. Isaacs. Data Abstraction Elephants: The Initial Diversity of Data Representations and Mental Models. To appear in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. ACM, 2023.
Data (OSF.io) | Codes Github

S. A. Sakin, A. Bigelow, R. Tohid, C. Scully-Allison, C. Scheidegger, S. R. Brandt, C. Taylor, K. A. Huck, H. Kaiser, and K. E. Isaacs. Traveler: Navigating Task Parallel Traces for Performance Analysis. IEEE Transactions on Visualization and Computer Graphics, Proceedings of IEEE VIS 2022. 29(1):788-797, January 2023.
PDF (Arxiv) | DOI

R. Faust, C. Scheidegger, K. E. Isaacs, W. Z. Bernstein, M. Sharp, and C. North. Interactive Visualization for Data Science Scripts. In Proceedings of Visualization in Data Science, October 2022.
DOI

S. Devkota, M. LeGendre, A. Kunen, P. Aschwanden, and K. E. Isaacs. Domain-centered support for layout, tasks, and specification for control flow graph visualization. Inn Proceedings of the 10th IEEE Working Conference on Software Visualization (VISSOFT), Oct. 2022.
PDF (Arxiv) | DOI | Supplemental Material | Github

I. Lumsden, J. Luettgau, V. Lama, C. Scully-Allison, S. Brink, K. E. Isaacs, O. Pearce, and M. Taufer. Enabling call path querying in hatchet to identify performance bottlenecks in scientific applications. In Proceedings of the 18th IEEE International eScience Conference (eScience 2022), Oct. 2022.
PDF (OSTI) | DOI

M. Ramirez-Andreotta, R. Walls, K. Youens-Clark, K. Blumberg, K. E. Isaacs, D. Kaufmann, and R. M. Maier. Alleviating environmental health disparities through community science and data integration. Frontiers in Sustainable Food Systems, 5, June 2021.
Article (Frontiers HTML)

A. Bigelow, K. Williams, and K. E. Isaacs. Guidelines for Pursuing and Revealing Data Abstractions. IEEE Transactions on Visualization and Computer Graphics, Proceedings of InfoVis '20. 27:1503-1513, February 2021.
PDF (Arxiv) | Survey Data | Codes (OSF)

S. Devkota, P. Aschwanden, A. Kunen, M. Legendre, and K. E. Isaacs. CcNav: Understanding the Compilation of Binary Code. IEEE Transactions on Visualization and Computer Graphics, Proceedings of VAST '20. 27:667-677, February 2021.
PDF (Arxiv)

S. R. Brandt, B. Hasheminezhad, N. Wu, S. A. Sakin, A. R. Bigelow, K. E. Isaacs, K. Huck, H. Kaiser. Distributed Asynchronous Array Computing with the Jetlag Environment. Proceedings of the 9th Workshop on Python for High-Perforrmance and Scientific Computing (PyHPC). November 2020.

S. Brink, I. Lumsden, C. Scully-Allison, K. Williams, O. Pearce, T. Gamblin, M. Taufer, K. E. Isaacs, and A. Bhatele. Usability and Performance Improvements in Hatchet. Proceedings of the 2020 IEEE/ACM International Workshop on HPC User Support Tools (HUST) and Workshop on Programming and Performance Visualization Tools (ProTools), held in conjunction with SC20, November 2020.

S. R. Brandt, A. Bigelow, S. A. Sakin, K. Willliams, K. E. Isaacs, K. Huck, R. Tohid, B. Wagle, S. Shirzad, and H. Kaiser. JetLag: An Interactive, Asynchronous Array Computing Environment. In PEARC '20: Practice and Experience in Advanced Research Computing.July 2020.
DOI

K. Williams, A. Bigelow, and K. Isaacs. Visualizing a Moving Target: A Design Study on Task Parallel Programs in the Presence of Evolving Data and Concerns. IEEE Transactions on Visualization and Computer Graphics, Proceedings of InfoVis '19. 26(1):1118-1128, 2020.
PDF (Arxiv) | DOI | Code

S. Devkota, A. R. Ahmed, F. De Luca, K. Isaacs, and S. Kobourov. Stress-Plus-X (SPX) Graph Layout. Proceedings of Graph Drawing 2019.
PDF (Arxiv)

K. E. Isaacs and Todd Gamblin. Preserving Command Line Workflow for a Package Management System using ASCII DAG Visualization. IEEE Transactions on Visualization and Computer Graphics. 25(9):2804-2820, 2019.
PDF | DOI | Code | Survey of Graph Tools used by Github Projects

B. Lee, K. Isaacs, D. A. Szafir, G. E. Marai, C. Turkay, M. Tory, S. Carpendale, A. Endert. Broadening Intellectual Diversity in Visualization Research Papers. Computer Graphics & Applications, Visualization Viewpoints, July 2019.
DOI

R. Tohid, B. Wagle, S. Shirzad, P. Diehl, A. Serio, A. Kheirkhahan, P. Amini, K. Williams, K. Isaacs, K. Huck, S. Brandt, and H. Kaiser. Asynchronous Execution of Python Code on Task-Based Runtime Systems. Proceedings of 2018 IEEE/ACM 4th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2). November 2018.
DOI

S. Cheng, W. Zhong, K. E. Isaacs, and K. Mueller. Visualizing the topology and data traffic of multi-dimensional torus interconnect networks. IEEE Access. September 2018.
DOI

S. Devkota and K. E. Isaacs. CFGExplorer: Designing a Visual Control Flow Analytics System around Basic Program Analysis Operations. Computer Graphics Forum (Proceedings of EuroVis). July 2018.
PDF | DOI | Code

H. Purchase, K. E. Isaacs, T. Bueti, B. Hastings, A. Kassan, A. Kim, and S. van Hoesen. A Classification of Infographics. Proceedings of the 10th International Conference on the Theory and Application of Diagrams, pp. 210-218, June 2018.
PDF | DOI

M. M. Strout, S. Debray, K. E. Isaacs, B. Kreaseck, J. Cárdenas-Rodríguez, B. Hurwitz, K. Volk, S. Badger, J. Bartels, I. Bertolacci, S. Devkota, A. Encinas, B. Gaska, B. Neth, T. Sackos, J. Stephens, S. Willer, and B. Yadergari. Language-Agnostic Optimization and Parallelization for Interpreted Languages. In Proceedings of the 30th Workshop on Languages and Compilers for Parallel Computing (LCPC), October 2017.
DOI

K. E. Isaacs, T. Gamblin, A. Bhatele, M. Schulz, B. Hamann, and P.-T. Bremer. Ordering traces logically to identify lateness in message passing programs. IEEE Transactions on Parallel and Distributed Systems, 27(3):829-840, 2016.
PDF | DOI | Code

K. E. Isaacs, A. Bhatele, J. Lifflander, D. Boehme, T. Gamblin, M. Schulz, B. Hamann, and P.-T. Bremer. Recovering logical structure from Charm++ event traces. In Proceedings of the ACM/IEEE Conference on Supercomputing (SC15), SC '15, Nov. 2015.
PDF | DOI

K. E. Isaacs, P.-T. Bremer, I. Jusufi, T. Gamblin, A. Bhatele, M. Schulz, and B. Hamann. Combing the communication hairball: Visualizing large-scale parallel execution traces using logical time. IEEE Transactions on Visualization and Computer Graphics, Proceedings of InfoVis ’14, 20(12):2349–2358, 2014.
PDF | DOI | Video Preview | Code

A. Bhatele, N. Jain, K. E. Isaacs, R. Buch, T. Gamblin, S. H. Langer, and L. V. Kalé. Optimizing the performance of parallel applications on a 5D torus via task mapping. In Proceedings of IEEE International Conference on High Performance Computing, HiPC ’14, Dec. 2014.
PDF | DOI

C. M. McCarthy, K. E. Isaacs, A. Bhatele, P.-T. Bremer, and B. Hamann. Visualizing the five-dimensional torus network of the IBM Blue Gene/Q. In Proceedings of the 1st Workshop on Visual Performance Analysis, pages 24 – 27, Nov. 2014.
PDF | DOI

K. E. Isaacs, A. Giménez, I. Jusufi, T. Gamblin, A. Bhatele, M. Schulz, B. Hamann, and P.-T. Bremer. State of the art of performance visualization. In Eurographics/IEEE Conference on Visualization State-of-the-Art Reports, EuroVis ’14, 2014.
PDF | DOI | Companion Website

A. Bhatele, K. Mohror, S. H. Langer, and K. E. Isaacs. There goes the neighborhood: performance degradation due to nearby jobs. In Proceedings of the ACM/IEEE Conference on Supercomputing (SC13), SC ’13, Nov. 2013.
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E. A. Dinsdale, R. A. Edwards, B. A. Bailey, I. Tuba, S. Akhter, K. McNair, R. Schmieder, N. Apkarian, M. Creek, E. Guan, M. Hernandez, K. Isaacs, C. Peterson, T. Regh, and V. Ponomarenko. Multivariate analysis of functional metagenomes. Frontiers in Genetics, 4(41), 2013.

A. G. Landge, J. A. Levine, K. E. Isaacs, A. Bhatele, T. Gamblin, M. Schulz, S. H. Langer, P.-T. Bremer, and V. Pascucci. Visualizing network traffic to understand the performance of massively parallel simulations. IEEE Transactions on Visualization and Computer Graphics, Proceedings of InfoVis ’12, 18(12):2467–2476, 2012.
PDF | DOI

A. Bhatele, T. Gamblin, K. E. Isaacs, B. T. N. Gunney, M. Schulz, P.-T. Bremer, and B. Hamann. Novel views of performance data to analyze large-scale adaptive applications. In Proceedings of ACM/IEEE Conference on Supercomputing (SC12), SC ’12, Nov. 2012.
PDF | DOI

A. Bhatele, T. Gamblin, S. H. Langer, P.-T. Bremer, E. W. Draeger, B. Hamann, K. E. Isaacs, A. G. Landge, J. A. Levine, V. Pascucci, M. Schulz, and C. H. Still. Mapping applications with collectives over sub-communicators on torus networks. In Proceedings of ACM/IEEE Conference on Supercomputing (SC12), SC ’12, Nov. 2012.
PDF | DOI

M. Schulz, A. Bhatele, P.-T. Bremer, T. Gamblin, K. Isaacs, J. A. Levine, and V. Pascucci. Creating a tool set for optimizing topology-aware node mappings. In 5th Parallel Tools Workshop, Sept. 2011. PDF

Extended Abstracts

C. Scully-Allison, O. Pearce, and K. E. Isaacs. Missing the trees for the branches: Graphical scripting interaction with large-scale calling context trees. In Proceedings of the 2021 SC Companion: ACM/IEEE Conference on Supercomputing, SCC ’12, Nov. 2021, 1st Place SC ACM Student Research Competition, Graduate Division.

K. E. Isaacs, T. Gamblin, A. Bhatele, P.-T. Bremer, M. Schulz, and B. Hamann. Extracting logical structure and identifying stragglers in parallel execution traces. In Proceedings 19th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP ’14, pages 397–398, 2014.
DOI

K. E. Isaacs, A. G. Landge, T. Gamblin, P.-T. Bremer, V. Pascucci, and B. Hamann. Exploring performance data with Boxfish. In Proceedings of the 2012 SC Companion: ACM/IEEE Conference on Supercomputing, SCC ’12, pages 1380–1381, Nov. 2012.
PDF | DOI | Code

Presentations

K. Isaacs. Enabling Fine-Grained Exploration of Application Performance through Visualization. Invited Talk. Los Alamos National Laboratory, Los Alamos, NM, USA, August 8, 2018.

K. Isaacs. The state of the practice of performance visualization. Keynote. 3rd International Workshop on Visual Performance Analysis, VPA '16, Salt Lake City, UT, USA, November 18, 2016.

K. Isaacs. Understanding parallel computing through visualization. Computer Science Colloquium, Sonoma State University, Sonoma, CA, USA, November 12, 2015.

K. Isaacs. An organized view of MPI and Charm++ traces. Contributed Talk. 13th Annual Workshop on Charm++ and its Applications, Charm++ Workshop ’15, Urbana, IL, USA, May 7, 2015.

K. E. Isaacs. Boxfish: Mapping performance data and visualizations. Invited Talk. Lawrence Berkeley National Laboratory, Berkeley, CA, USA, March 26, 2015.

K. E. Isaacs and T. Gamblin. Introduction to performance analysis. Workshop on Visualization and Analysis of Performance on Large-scale Software, Atlanta, Georgia USA, October 14, 2013.

K. Isaacs. A statistical method for environmental prediction in metagenomic samples. Contributed Talk. Joint Math Meetings, San Francisco, California USA, January 14, 2010.