C. Scully-Allison, I. Lumsden, K. Williams, J. Bartels, M. Taufer, S. Brink, A. Bhatele, O. Pearce and K. E. Isaacs.
Design Concerns for Integrated Scripting and Interactive Visualization in Notebook Environments.
To appear in IEEE Transactions on
Visualization and Computer Graphics.
DOI
S. Wang, H. Yan, K. E. Isaacs, and Y. Sun. Visual
Exploratory Analysis for Designing Large-Scale Network-on-Chip Architectures:
A Domain Expert-Led Design Study. IEEE Transactions on
Visualization and Computer Graphics.
DOI
S. Brink, M. McKinsey, D. Boehme, C. Scully-Allison, I.
Lumsden, D. Hawkins, T. Burgess, V. Lama, J. Luettagau, K. E.
Isaacs, M. Taufer, and O. Pearce. Thicket: Seeing the Performance
Experiment FOrest for the Individual Run Trees. In HPDC '23: The 32nd
International Symposium on High-Performance Parallel and Distributed
Computing. ACM, 2023.
PDF
K. Williams, A. Bigelow, and K. E. Isaacs. Data
Abstraction Elephants: The Initial Diversity of Data Representations and Mental
Models. In Proceedings of the 2023 CHI Conference on Human Factors
in Computing Systems. ACM, 2023.
HTML (ACM) | 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
R. Tohid, S. Shirzad, C. Taylor, S. Sakin, K. E. Isaacs,
and H. Kaiser. "Halide Code Generation Framework in Phylanx. In: Singer, J.,
Elkhatib, Y., Blanco Heras, D., Diehl, P., Brown, N., Ilic, A. (eds) Euro-Par
2022: Parallel Processing Workshops. Euro-Par 2022. Lecture Notes in Computer
Science, vol 13835. Springer, Cham. August 2022
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) |
Supplemental Materials
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.
PDF |
DOI
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
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
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.