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Todd Gamblin

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affiliation: Lawrence Livermore National Laboratory, Livermore, CA, USA
affiliation: University of North Carolina at Chapel Hill, Renaissance Computing Institute, NC, USA

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Books and Theses

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2009
[b1]
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Todd Gamblin:
Scalable performance measurement and analysis. University of North Carolina, Chapel Hill, USA, 2009

Journal Articles

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2023
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Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Stephanie Brink, Olga Pearce, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma:
Scalable Comparative Visualization of Ensembles of Call Graphs. IEEE Trans. Vis. Comput. Graph. 29(3): 1691-1704 (2023)
2022
[j18]
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Todd Gamblin, Daniel S. Katz:
Overcoming Challenges to Continuous Integration in HPC. Comput. Sci. Eng. 24(6): 54-59 (2022)
[j17]
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Michael R. Wyatt II, Stephen Herbein, Todd Gamblin, Michela Taufer:
AI4IO: A suite of AI-based tools for IO-aware scheduling. Int. J. High Perform. Comput. Appl. 36(3): 370-387 (2022)
2021
[j16]
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Huu Tan Nguyen, Abhinav Bhatele, Nikhil Jain, Suraj P. Kesavan, Harsh Bhatia, Todd Gamblin, Kwan-Liu Ma, Peer-Timo Bremer:
Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow. IEEE Trans. Vis. Comput. Graph. 27(4): 2455-2468 (2021)
2019
[j15]
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Katherine E. Isaacs, Todd Gamblin:
Preserving Command Line Workflow for a Package Management System Using ASCII DAG Visualization. IEEE Trans. Vis. Comput. Graph. 25(9): 2804-2820 (2019)
2018
[j14]
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Prasanna Balaprakash, Jack J. Dongarra, Todd Gamblin, Mary W. Hall, Jeffrey K. Hollingsworth, Boyana Norris, Richard W. Vuduc:
Autotuning in High-Performance Computing Applications. Proc. IEEE 106(11): 2068-2083 (2018)
[j13]
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Alfredo Giménez, Todd Gamblin, Ilir Jusufi, Abhinav Bhatele, Martin Schulz, Peer-Timo Bremer, Bernd Hamann:
MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors. IEEE Trans. Vis. Comput. Graph. 24(7): 2180-2193 (2018)
2017
[j12]
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Roscoe A. Bartlett, Irina Demeshko, Todd Gamblin, Glenn Hammond, Michael A. Heroux, Jeffrey Johnson, Alicia M. Klinvex, Xiaoye S. Li, Lois Curfman McInnes, J. David Moulton, Daniel Osei-Kuffuor, Jason Sarich, Barry Smith, James M. Willenbring, Ulrike Meier Yang:
xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit. Supercomput. Front. Innov. 4(1): 69-82 (2017)
2016
[j11]
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Ignacio Laguna, David F. Richards, Todd Gamblin, Martin Schulz, Bronis R. de Supinski, Kathryn M. Mohror, Howard Pritchard:
Evaluating and extending user-level fault tolerance in MPI applications. Int. J. High Perform. Comput. Appl. 30(3): 305-319 (2016)
[j10]
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Katherine E. Isaacs, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann, Peer-Timo Bremer:
Ordering Traces Logically to Identify Lateness in Message Passing Programs. IEEE Trans. Parallel Distributed Syst. 27(3): 829-840 (2016)
2015
[j9]
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Ignacio Laguna, Dong H. Ahn, Bronis R. de Supinski, Todd Gamblin, Gregory L. Lee, Martin Schulz, Saurabh Bagchi, Milind Kulkarni, Bowen Zhou, Zhezhe Chen, Feng Qin:
Debugging high-performance computing applications at massive scales. Commun. ACM 58(9): 72-81 (2015)
[j8]
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Peer-Timo Bremer, Bernd Mohr, Valerio Pascucci, Martin Schulz, Todd Gamblin, Holger Brunst:
Connecting Performance Analysis and Visualization (Dagstuhl Perspectives Workshop 14022). Dagstuhl Manifestos 5(1): 1-24 (2015)
[j7]
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Ignacio Laguna, Dong H. Ahn, Bronis R. de Supinski, Saurabh Bagchi, Todd Gamblin:
Diagnosis of Performance Faults in LargeScale MPI Applications via Probabilistic Progress-Dependence Inference. IEEE Trans. Parallel Distributed Syst. 26(5): 1280-1289 (2015)
2014
[j6]
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Katherine E. Isaacs, Peer-Timo Bremer, Ilir Jusufi, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann:
Combing the Communication Hairball: Visualizing Parallel Execution Traces using Logical Time. IEEE Trans. Vis. Comput. Graph. 20(12): 2349-2358 (2014)
2013
[j5]
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Lukasz G. Szafaryn, Todd Gamblin, Bronis R. de Supinski, Kevin Skadron:
Trellis: Portability across architectures with a high-level framework. J. Parallel Distributed Comput. 73(10): 1400-1413 (2013)
[j4]
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Barry Rountree, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, David K. Lowenthal, Guy Cobb, Henry M. Tufo:
Parallelizing heavyweight debugging tools with mpiecho. Parallel Comput. 39(3): 156-166 (2013)
2012
[j3]
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Sandeep Budanur, Frank Mueller, Todd Gamblin:
Memory Trace Compression and Replay for SPMD Systems Using Extended PRSDs. Comput. J. 55(2): 206-217 (2012)
[j2]
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Aaditya G. Landge, Joshua A. Levine, Abhinav Bhatele, Katherine E. Isaacs, Todd Gamblin, Martin Schulz, Steve H. Langer, Peer-Timo Bremer, Valerio Pascucci:
Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations. IEEE Trans. Vis. Comput. Graph. 18(12): 2467-2476 (2012)
2011
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Sandeep Budanur, Frank Mueller, Todd Gamblin:
Memory Trace Compression and Replay for SPMD Systems using Extended PRSDs? SIGMETRICS Perform. Evaluation Rev. 38(4): 30-36 (2011)

Conference and Workshop Papers

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2023
[c81]
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Donald Pinckney, Federico Cassano, Arjun Guha, Jonathan Bell, Massimiliano Culpo, Todd Gamblin:
Flexible and Optimal Dependency Management via Max-SMT. ICSE 2023: 1418-1429
[c80]
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Olga Pearce, Alec Scott, Gregory Becker, Riyaz Haque, Nathan Hanford, Stephanie Brink, Doug Jacobsen, Heidi Poxon, Jens Domke, Todd Gamblin:
Towards Collaborative Continuous Benchmarking for HPC. SC Workshops 2023: 627-635
2022
[c79]
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Daniel Nichols, Aniruddha Marathe, Kathleen Shoga, Todd Gamblin, Abhinav Bhatele:
Resource Utilization Aware Job Scheduling to Mitigate Performance Variability. IPDPS 2022: 335-345
[c78]
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Harshitha Menon, Konstantinos Parasyris, Tom Scogland, Todd Gamblin:
Searching for High-Fidelity Builds Using Active Learning. MSR 2022: 179-190
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Farid Zakaria, Thomas R. W. Scogland, Todd Gamblin, Carlos Maltzahn:
Mapping Out the HPC Dependency Chaos. SC 2022: 34:1-34:12
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Todd Gamblin, Massimiliano Culpo, Gregory Becker, Sergei Shudler:
Using Answer Set Programming for HPC Dependency Solving. SC 2022: 35:1-35:15
2021
[c75]
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Ivy Peng, Ian Karlin, Maya B. Gokhale, Kathleen Shoga, Matthew P. LeGendre, Todd Gamblin:
A Holistic View of Memory Utilization on HPC Systems: Current and Future Trends. MEMSYS 2021: 14:1-14:11
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Chad Wood, Giorgis Georgakoudis, David Beckingsale, David Poliakoff, Alfredo Giménez, Kevin A. Huck, Allen D. Malony, Todd Gamblin:
Artemis: Automatic Runtime Tuning of Parallel Execution Parameters Using Machine Learning. ISC 2021: 453-472
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Chunhua Liao, Anjia Wang, Giorgis Georgakoudis, Bronis R. de Supinski, Yonghong Yan, David Beckingsale, Todd Gamblin:
Extending OpenMP for Machine Learning-Driven Adaptation. WACCPD@SC 2021: 49-69
2020
[c72]
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Tao Wang, Nikhil Jain, David Böhme, David Beckingsale, Frank Mueller, Todd Gamblin:
CodeSeer: input-dependent code variants selection via machine learning. ICS 2020: 43:1-43:11
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Michael R. Wyatt II, Stephen Herbein, Kathleen Shoga, Todd Gamblin, Michela Taufer:
CanarIO: Sounding the Alarm on IO-Related Performance Degradation. IPDPS 2020: 73-83
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Harshitha Menon, Abhinav Bhatele, Todd Gamblin:
Auto-tuning Parameter Choices in HPC Applications using Bayesian Optimization. IPDPS 2020: 831-840
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Massimiliano Culpo, Gregory Becker, Carlos Eduardo Arango Gutierrez, Kenneth Hoste, Todd Gamblin:
archspec: A library for detecting, labeling, and reasoning about microarchitectures. CANOPIE-HPC@SC 2020: 45-52
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Stephanie Brink, Ian Lumsden, Connor Scully-Allison, Katy Williams, Olga Pearce, Todd Gamblin, Michela Taufer, Katherine E. Isaacs, Abhinav Bhatele:
Usability and Performance Improvements in Hatchet. HUST/ProTools@SC 2020: 49-58
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Tal Ben-Nun, Todd Gamblin, Daisy S. Hollman, Hari Krishnan, Chris J. Newburn:
Workflows are the New Applications: Challenges in Performance, Portability, and Productivity. P3HPC@SC 2020: 57-69
2019
[c66]
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Tao Wang, Nikhil Jain, David Beckingsale, David Böhme, Frank Mueller, Todd Gamblin:
FuncyTuner: Auto-tuning Scientific Applications With Per-loop Compilation. ICPP 2019: 91:1-91:10
[c65]
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Abhinav Bhatele, Nikhil Jain, Misbah Mubarak, Todd Gamblin:
Analyzing Cost-Performance Tradeoffs of HPC Network Designs under Different Constraints using Simulations. SIGSIM-PADS 2019: 1-12
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Abhinav Bhatele, Stephanie Brink, Todd Gamblin:
Hatchet: pruning the overgrowth in parallel profiles. SC 2019: 20:1-20:21
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Samuel Knight, Jeremiah J. Wilke, Todd Gamblin:
Using Malleable Task Scheduling to Accelerate Package Manager Installations. HUST/SE-HER/WIHPC@SC 2019: 28-48
[c62]
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Ian Karlin, Yoonho Park, Bronis R. de Supinski, Peng Wang, Bert Still, David Beckingsale, Robert Blake, Tong Chen, Guojing Cong, Carlos H. A. Costa, Johann Dahm, Giacomo Domeniconi, Thomas Epperly, Aaron Fisher, Sara Kokkila Schumacher, Steven H. Langer, Hai Le, Eun Kyung Lee, Naoya Maruyama, Xinyu Que, David F. Richards, Björn Sjögreen, Jonathan Wong, Carol S. Woodward, Ulrike Meier Yang, Xiaohua Zhang, Bob Anderson, David Appelhans, Levi Barnes, Peter D. Barnes Jr., Sorin Bastea, David Böhme, Jamie A. Bramwell, James M. Brase, José R. Brunheroto, Barry Chen, Charway R. Cooper, Tony Degroot, Robert D. Falgout, Todd Gamblin, David J. Gardner, James N. Glosli, John A. Gunnels, Max P. Katz, Tzanio V. Kolev, I-Feng W. Kuo, Matthew P. LeGendre, Ruipeng Li, Pei-Hung Lin, Shelby Lockhart, Kathleen McCandless, Claudia Misale, Jaime H. Moreno, Rob Neely, Jarom Nelson, Rao Nimmakayala, Kathryn M. O'Brien, Kevin O'Brien, Ramesh Pankajakshan, Roger Pearce, Slaven Peles, Phil Regier, Steven C. Rennich, Martin Schulz, Howard Scott, James C. Sexton, Kathleen Shoga, Shiv Sundram, Guillaume Thomas-Collignon, Brian Van Essen, Alexey Voronin, Bob Walkup, Lu Wang, Chris Ward, Hui-Fang Wen, Daniel A. White, Christopher Young, Cyril Zeller, Edward Zywicz:
Preparation and optimization of a diverse workload for a large-scale heterogeneous system. SC 2019: 32:1-32:17
2018
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Michael R. Wyatt II, Stephen Herbein, Todd Gamblin, Adam Moody, Dong H. Ahn, Michela Taufer:
PRIONN: Predicting Runtime and IO using Neural Networks. ICPP 2018: 46:1-46:12
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Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin:
Bootstrapping Parameter Space Exploration for Fast Tuning. ICS 2018: 385-395
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Jayaraman J. Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, Nikhil Jain, Tanzima Z. Islam, Abhinav Bhatele, Jae-Seung Yeom, Todd Gamblin:
PADDLE: Performance Analysis Using a Data-Driven Learning Environment. IPDPS 2018: 784-793
2017
[c58]
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David Beckingsale, Olga Pearce, Ignacio Laguna, Todd Gamblin:
Apollo: Reusable Models for Fast, Dynamic Tuning of Input-Dependent Code. IPDPS 2017: 307-316
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Hao Xu, Shasha Wen, Alfredo Giménez, Todd Gamblin, Xu Liu:
DR-BW: Identifying Bandwidth Contention in NUMA Architectures with Supervised Learning. IPDPS 2017: 367-376
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Nikhil Jain, Abhinav Bhatele, Xiang Ni, Todd Gamblin, Laxmikant V. Kalé:
Partitioning Low-Diameter Networks to Eliminate Inter-Job Interference. IPDPS 2017: 439-448
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Todd Gamblin:
REPPAR Keynote. IPDPS Workshops 2017: 1560
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Aniruddha Marathe, Rushil Anirudh, Nikhil Jain, Abhinav Bhatele, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Jae-Seung Yeom, Barry Rountree, Todd Gamblin:
Performance modeling under resource constraints using deep transfer learning. SC 2017: 31
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Alfredo Giménez, Todd Gamblin, Abhinav Bhatele, Chad Wood, Kathleen Shoga, Aniruddha Marathe, Peer-Timo Bremer, Bernd Hamann, Martin Schulz:
ScrubJay: deriving knowledge from the disarray of HPC performance data. SC 2017: 35
[c52]
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Nikhil Jain, Abhinav Bhatele, Louis H. Howell, David Böhme, Ian Karlin, Edgar A. León, Misbah Mubarak, Noah Wolfe, Todd Gamblin, Matthew L. Leininger:
Predicting the performance impact of different fat-tree configurations. SC 2017: 50
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Chad Wood, Matthew Larsen, Alfredo Giménez, Kevin A. Huck, Cyrus Harrison, Todd Gamblin, Allen D. Malony:
Projecting Performance Data over Simulation Geometry Using SOSflow and ALPINE. ESPT/VPA@SC 2017: 201-218
2016
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Ryan McKenna, Stephen Herbein, Adam Moody, Todd Gamblin, Michela Taufer:
Machine Learning Predictions of Runtime and IO Traffic on High-End Clusters. CLUSTER 2016: 255-258
[c49]
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Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Nancy M. Amato:
MPMD Framework for Offloading Load Balance Computation. IPDPS 2016: 943-952
[c48]
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Kirk W. Cameron, Todd Gamblin, Dimitrios S. Nikolopoulos:
VarSys Introduction. IPDPS Workshops 2016: 1068
[c47]
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Shuaiwen Leon Song, Todd Gamblin:
IPDRM Introduction and Committees. IPDPS Workshops 2016: 1726
[c46]
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Subrata Mitra, Suhas Javagal, Amiya Kumar Maji, Todd Gamblin, Adam Moody, Stephen Lien Harrell, Saurabh Bagchi:
A Study of Failures in Community Clusters: The Case of Conte. ISSRE Workshops 2016: 189-196
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Gregory Becker, Peter Scheibel, Matthew P. LeGendre, Todd Gamblin:
Managing Combinatorial Software Installations with Spack. HUST@SC 2016: 14-23
[c44]
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Huu Tan Nguyen, Lai Wei, Abhinav Bhatele, Todd Gamblin, David Böhme, Martin Schulz, Kwan-Liu Ma, Peer-Timo Bremer:
VIPACT: A Visualization Interface for Analyzing Calling Context Trees. VPA@SC 2016: 25-28
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Chad Wood, Sudhanshu Sane, Daniel A. Ellsworth, Alfredo Giménez, Kevin A. Huck, Todd Gamblin, Allen D. Malony:
A Scalable Observation System for Introspection and In Situ Analytics. ESPT@SC 2016: 42-49
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Nikhil Jain, Abhinav Bhatele, Sam White, Todd Gamblin, Laxmikant V. Kalé:
Evaluating HPC networks via simulation of parallel workloads. SC 2016: 154-165
[c41]
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Tanzima Z. Islam, Jayaraman J. Thiagarajan, Abhinav Bhatele, Martin Schulz, Todd Gamblin:
A machine learning framework for performance coverage analysis of proxy applications. SC 2016: 538-549
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David Böhme, Todd Gamblin, David Beckingsale, Peer-Timo Bremer, Alfredo Giménez, Matthew P. LeGendre, Olga Pearce, Martin Schulz:
Caliper: performance introspection for HPC software stacks. SC 2016: 550-560
2015
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Abhinav Bhatele, Andrew R. Titus, Jayaraman J. Thiagarajan, Nikhil Jain, Todd Gamblin, Peer-Timo Bremer, Martin Schulz, Laxmikant V. Kalé:
Identifying the Culprits Behind Network Congestion. IPDPS 2015: 113-122
[c38]
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Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Nancy M. Amato:
Decoupled load balancing. PPoPP 2015: 267-268
[c37]
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Benafsh Husain, Alfredo Giménez, Joshua A. Levine, Todd Gamblin, Peer-Timo Bremer:
Relating memory performance data to application domain data using an integration API. VPA@SC 2015: 5:1-5:8
[c36]
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Todd Gamblin, Matthew P. LeGendre, Michael R. Collette, Gregory L. Lee, Adam Moody, Bronis R. de Supinski, Scott Futral:
The Spack package manager: bringing order to HPC software chaos. SC 2015: 40:1-40:12
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Katherine E. Isaacs, Abhinav Bhatele, Jonathan Lifflander, David Böhme, Todd Gamblin, Martin Schulz, Bernd Hamann, Peer-Timo Bremer:
Recovering logical structure from Charm++ event traces. SC 2015: 49:1-49:12
2014
[c34]
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Kento Sato, Kathryn M. Mohror, Adam Moody, Todd Gamblin, Bronis R. de Supinski, Naoya Maruyama, Satoshi Matsuoka:
A User-Level InfiniBand-Based File System and Checkpoint Strategy for Burst Buffers. CCGRID 2014: 21-30
[c33]
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Abhinav Bhatele, Nikhil Jain, Katherine E. Isaacs, Ronak Buch, Todd Gamblin, Steven H. Langer, Laxmikant V. Kalé:
Optimizing the performance of parallel applications on a 5D torus via task mapping. HiPC 2014: 1-10
[c32]
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Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Tom Arsenlis, Nancy M. Amato:
Load balancing n-body simulations with highly non-uniform density. ICS 2014: 113-122
[c31]
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Kento Sato, Adam Moody, Kathryn M. Mohror, Todd Gamblin, Bronis R. de Supinski, Naoya Maruyama, Satoshi Matsuoka:
FMI: Fault Tolerant Messaging Interface for Fast and Transparent Recovery. IPDPS 2014: 1225-1234
[c30]
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Subrata Mitra, Ignacio Laguna, Dong H. Ahn, Saurabh Bagchi, Martin Schulz, Todd Gamblin:
Accurate application progress analysis for large-scale parallel debugging. PLDI 2014: 193-203
[c29]
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Katherine E. Isaacs, Todd Gamblin, Abhinav Bhatele, Peer-Timo Bremer, Martin Schulz, Bernd Hamann:
Extracting logical structure and identifying stragglers in parallel execution traces. PPoPP 2014: 397-398
[c28]
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Ignacio Laguna, David F. Richards, Todd Gamblin, Martin Schulz, Bronis R. de Supinski:
Evaluating User-Level Fault Tolerance for MPI Applications. EuroMPI/ASIA 2014: 57
[c27]
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Alfredo Giménez, Todd Gamblin, Barry Rountree, Abhinav Bhatele, Ilir Jusufi, Peer-Timo Bremer, Bernd Hamann:
Dissecting On-Node Memory Access Performance: A Semantic Approach. SC 2014: 166-176
[c26]
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Katherine E. Isaacs, Alfredo Giménez, Ilir Jusufi, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann, Peer-Timo Bremer:
State of the Art of Performance Visualization. EuroVis (STARs) 2014
2013
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Wolfgang Frings, Dong H. Ahn, Matthew P. LeGendre, Todd Gamblin, Bronis R. de Supinski, Felix Wolf:
Massively parallel loading. ICS 2013: 389-398
[c24]
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Dong H. Ahn, Michael J. Brim, Bronis R. de Supinski, Todd Gamblin, Gregory L. Lee, Matthew P. LeGendre, Barton P. Miller, Adam Moody, Martin Schulz:
Efficient and Scalable Retrieval Techniques for Global File Properties. IPDPS 2013: 369-380
[c23]
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Martin Schulz, James F. Belak, Abhinav Bhatele, Peer-Timo Bremer, Greg Bronevetsky, Marc Casas, Todd Gamblin, Katherine E. Isaacs, Ignacio Laguna, Joshua A. Levine, Valerio Pascucci, David F. Richards, Barry Rountree:
Performance Analysis Techniques for the Exascale Co-Design Process. PARCO 2013: 19-32
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Nikhil Jain, Abhinav Bhatele, Michael P. Robson, Todd Gamblin, Laxmikant V. Kalé:
Predicting application performance using supervised learning on communication features. SC 2013: 95:1-95:12
2012
[c21]
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Ignacio Laguna, Dong H. Ahn, Bronis R. de Supinski, Saurabh Bagchi, Todd Gamblin:
Probabilistic diagnosis of performance faults in large-scale parallel applications. PACT 2012: 213-222
[c20]
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Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Nancy M. Amato:
Quantifying the effectiveness of load balance algorithms. ICS 2012: 185-194
[c19]
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Spyros Lyberis, Polyvios Pratikakis, Dimitrios S. Nikolopoulos, Martin Schulz, Todd Gamblin, Bronis R. de Supinski:
The myrmics memory allocator: hierarchical, message-passing allocation for global address spaces. ISMM 2012: 15-24
[c18]
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Kento Sato, Naoya Maruyama, Kathryn M. Mohror, Adam Moody, Todd Gamblin, Bronis R. de Supinski, Satoshi Matsuoka:
Design and modeling of a non-blocking checkpointing system. SC 2012: 19
[c17]
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Abhinav Bhatele, Todd Gamblin, Katherine E. Isaacs, Brian T. N. Gunney, Martin Schulz, Peer-Timo Bremer, Bernd Hamann:
Novel views of performance data to analyze large-scale adaptive applications. SC 2012: 31
[c16]
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Abhinav Bhatele, Todd Gamblin, Steve H. Langer, Peer-Timo Bremer, Erik W. Draeger, Bernd Hamann, Katherine E. Isaacs, Aaditya G. Landge, Joshua A. Levine, Valerio Pascucci, Martin Schulz, Charles H. Still:
Mapping applications with collectives over sub-communicators on torus networks. SC 2012: 97
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Anshu Arya, Todd Gamblin, Bronis R. de Supinski, Laxmikant V. Kalé:
Abstract: Evaluating Topology Mapping via Graph Partitioning. SC Companion 2012: 1371
[c14]
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Anshu Arya, Todd Gamblin, Bronis R. de Supinski, Laxmikant V. Kalé:
Poster: Evaluation Topology Mapping via Graph Partitioning. SC Companion 2012: 1372
[c13]
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Katherine E. Isaacs, Aaditya G. Landge, Todd Gamblin, Peer-Timo Bremer, Valerio Pascucci, Bernd Hamann:
Abstract: Exploring Performance Data with Boxfish. SC Companion 2012: 1380-1381
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Vivek Kale, Todd Gamblin, Torsten Hoefler, Bronis R. de Supinski, William D. Gropp:
Abstract: Slack-Conscious Lightweight Loop Scheduling for Improving Scalability of Bulk-synchronous MPI Applications. SC Companion 2012: 1392
2011
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Martin Schulz, Joshua A. Levine, Peer-Timo Bremer, Todd Gamblin, Valerio Pascucci:
Interpreting Performance Data across Intuitive Domains. ICPP 2011: 206-215
[c10]
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Allison H. Baker, Todd Gamblin, Martin Schulz, Ulrike Meier Yang:
Challenges of Scaling Algebraic Multigrid Across Modern Multicore Architectures. IPDPS 2011: 275-286
[c9]
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Zoltán Szebenyi, Todd Gamblin, Martin Schulz, Bronis R. de Supinski, Felix Wolf, Brian J. N. Wylie:
Reconciling Sampling and Direct Instrumentation for Unintrusive Call-Path Profiling of MPI Programs. IPDPS 2011: 640-651
[c8]
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Martin Schulz, Abhinav Bhatele, Peer-Timo Bremer, Todd Gamblin, Katherine E. Isaacs, Joshua A. Levine, Valerio Pascucci:
Creating a Tool Set for Optimizing Topology-Aware Node Mappings. Parallel Tools Workshop 2011: 1-12
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Ignacio Laguna, Todd Gamblin, Bronis R. de Supinski, Saurabh Bagchi, Greg Bronevetsky, Dong H. Ahn, Martin Schulz, Barry Rountree:
Large scale debugging of parallel tasks with AutomaDeD. SC 2011: 50:1-50:10
2010
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Allison H. Baker, Robert D. Falgout, Todd Gamblin, Tzanio V. Kolev, Martin Schulz, Ulrike Meier Yang:
Scaling Algebraic Multigrid Solvers: On the Road to Exascale. CHPC 2010: 215-226
[c5]
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Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Robert J. Fowler, Daniel A. Reed:
Clustering performance data efficiently at massive scales. ICS 2010: 243-252
[c4]
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Frank Mueller, Xing Wu, Martin Schulz, Bronis R. de Supinski, Todd Gamblin:
ScalaTrace: Tracing, Analysis and Modeling of HPC Codes at Scale. PARA (2) 2010: 410-418
2008
[c3]
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Todd Gamblin, Robert J. Fowler, Daniel A. Reed:
Scalable methods for monitoring and detecting behavioral equivalence classes in scientific codes. IPDPS 2008: 1-12
[c2]
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Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Robert J. Fowler, Daniel A. Reed:
Scalable load-balance measurement for SPMD codes. SC 2008: 46
2006
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Robert J. Fowler, Todd Gamblin, Gopi Kandaswamy, Anirban Mandal, Allan Porterfield, Lavanya Ramakrishnan, Daniel A. Reed:
Challenges of Scale: When All Computing Becomes Grid Computing. High Performance Computing Workshop 2006: 186-206

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2021
[e2]
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Bronis R. de Supinski, Mary W. Hall, Todd Gamblin:
International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2021, St. Louis, Missouri, USA, November 14-19, 2021. ACM 2021, ISBN 978-1-4503-8442-1 [contents]
2015
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Chris Bording, Todd Gamblin, Vera Hansper:
Proceedings of the Second International Workshop on HPC User Support Tools, HUST 2015, Austin, Texas, USA, November 15, 2015. ACM 2015, ISBN 978-1-4503-4000-7 [contents]

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2023
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  - journals/corr/abs-2303-08873
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Giorgis Georgakoudis, Konstantinos Parasyris, Chunhua Liao, David Beckingsale, Todd Gamblin, Bronis R. de Supinski:
Machine Learning-Driven Adaptive OpenMP For Portable Performance on Heterogeneous Systems. CoRR abs/2303.08873 (2023)
[i9]
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  - journals/corr/abs-2303-17034
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Todd Gamblin, Daniel S. Katz:
Overcoming Challenges to Continuous Integration in HPC. CoRR abs/2303.17034 (2023)
[i8]
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  - journals/corr/abs-2306-17281
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Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele:
Modeling Parallel Programs using Large Language Models. CoRR abs/2306.17281 (2023)
2022
[i7]
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  - journals/corr/abs-2202-05223
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Harshitha Menon, Konstantinos Parasyris, Tom Scogland, Todd Gamblin:
Reliabuild: Searching for High-Fidelity Builds Using Active Learning. CoRR abs/2202.05223 (2022)
[i6]
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  - journals/corr/abs-2203-13737
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Donald Pinckney, Arjun Guha, Massimiliano Culpo, Todd Gamblin:
Using Solver-Aided Languages to Build Package Managers. CoRR abs/2203.13737 (2022)
[i5]
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Todd Gamblin, Massimiliano Culpo, Gregory Becker, Sergei Shudler:
Using Answer Set Programming for HPC Dependency Solving. CoRR abs/2210.08404 (2022)
[i4]
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  - journals/corr/abs-2211-05118
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Farid Zakaria, Thomas R. W. Scogland, Todd Gamblin, Carlos Maltzahn:
Mapping Out the HPC Dependency Chaos. CoRR abs/2211.05118 (2022)
2020
[i3]
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  - journals/corr/abs-2007-01395
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Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma:
Scalable Comparative Visualization of Ensembles of Call Graphs. CoRR abs/2007.01395 (2020)
2019
[i2]
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  - journals/corr/abs-1908-07544
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Katherine E. Isaacs, Todd Gamblin:
Preserving Command Line Workflow for a Package Management System using ASCII DAG Visualization. CoRR abs/1908.07544 (2019)
2017
[i1]
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  - journals/corr/BartlettDGHHJKL17
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Roscoe A. Bartlett, Irina Demeshko, Todd Gamblin, Glenn Hammond, Michael A. Heroux, Jeffrey Johnson, Alicia M. Klinvex, Xiaoye S. Li, Lois Curfman McInnes, J. David Moulton, Daniel Osei-Kuffuor, Jason Sarich, Barry Smith, James M. Willenbring, Ulrike Meier Yang:
xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit. CoRR abs/1702.08425 (2017)

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