Todd Gamblin

According to our database, Todd Gamblin authored at least 111 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

HPC and Cloud Convergence Beyond Technical Boundaries: Strategies for Economic Sustainability, Standardization, and Data Accessibility.

Michela Taufer, Daniel Milroy, Todd Gamblin, Andrew Jones, Bill Magro, Heidi Poxon, Seetharami R. Seelam

Computer, June, 2024

Providing a Flexible and Comprehensive Software Stack Via Spack, an Extreme-Scale Scientific Software Stack, and Software Development Kits.

James M. Willenbring, Sameer Suresh Shende, Todd Gamblin

Comput. Sci. Eng., 2024

Performance-Aligned LLMs for Generating Fast Code.

Daniel Nichols, Pranav Polasam, Harshitha Menon, Aniruddha Marathe, Todd Gamblin, Abhinav Bhatele

CoRR, 2024

HPC-Coder: Modeling Parallel Programs using Large Language Models.

Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele

Proceedings of the ISC High Performance 2024 Research Paper Proceedings (39th International Conference), 2024

Learning to Predict and Improve Build Successes in Package Ecosystems.

Harshitha Menon, Daniel Nichols, Abhinav Bhatele, Todd Gamblin

Proceedings of the 21st IEEE/ACM International Conference on Mining Software Repositories, 2024

An Exploration of Global Optimization Strategies for Autotuning OpenMP-based Codes.

Gregory Bolet, Giorgis Georgakoudis, Konstantinos Parasyris, Kirk W. Cameron, David Beckingsale, Todd Gamblin

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

2023

Scalable Comparative Visualization of Ensembles of Call Graphs.

Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Stephanie Brink, Olga Pearce, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma

IEEE Trans. Vis. Comput. Graph., March, 2023

Modeling Parallel Programs using Large Language Models.

Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele

CoRR, 2023

Machine Learning-Driven Adaptive OpenMP For Portable Performance on Heterogeneous Systems.

Giorgis Georgakoudis, Konstantinos Parasyris, Chunhua Liao, David Beckingsale, Todd Gamblin, Bronis R. de Supinski

CoRR, 2023

Towards Collaborative Continuous Benchmarking for HPC.

Olga Pearce, Alec Scott, Gregory Becker, Riyaz Haque, Nathan Hanford, Stephanie Brink, Doug Jacobsen, Heidi Poxon, Jens Domke, Todd Gamblin

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Flexible and Optimal Dependency Management via Max-SMT.

Donald Pinckney, Federico Cassano, Arjun Guha, Jonathan Bell, Massimiliano Culpo, Todd Gamblin

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

2022

AI4IO: A suite of AI-based tools for IO-aware scheduling.

Michael R. Wyatt II, Stephen Herbein, Todd Gamblin, Michela Taufer

Int. J. High Perform. Comput. Appl., 2022

Overcoming Challenges to Continuous Integration in HPC.

Todd Gamblin, Daniel S. Katz

Comput. Sci. Eng., 2022

Using Solver-Aided Languages to Build Package Managers.

Donald Pinckney, Arjun Guha, Massimiliano Culpo, Todd Gamblin

CoRR, 2022

Reliabuild: Searching for High-Fidelity Builds Using Active Learning.

Harshitha Menon, Konstantinos Parasyris, Tom Scogland, Todd Gamblin

CoRR, 2022

Mapping Out the HPC Dependency Chaos.

Farid Zakaria, Thomas R. W. Scogland, Todd Gamblin, Carlos Maltzahn

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Using Answer Set Programming for HPC Dependency Solving.

Todd Gamblin, Massimiliano Culpo, Gregory Becker, Sergei Shudler

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Searching for High-Fidelity Builds Using Active Learning.

Harshitha Menon, Konstantinos Parasyris, Tom Scogland, Todd Gamblin

Proceedings of the 19th IEEE/ACM International Conference on Mining Software Repositories, 2022

Resource Utilization Aware Job Scheduling to Mitigate Performance Variability.

Daniel Nichols, Aniruddha Marathe, Kathleen Shoga, Todd Gamblin, Abhinav Bhatele

Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

2021

Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow.

Huu Tan Nguyen, Abhinav Bhatele, Nikhil Jain, Suraj P. Kesavan, Harsh Bhatia, Todd Gamblin, Kwan-Liu Ma, Peer-Timo Bremer

IEEE Trans. Vis. Comput. Graph., 2021

Extending OpenMP for Machine Learning-Driven Adaptation.

Chunhua Liao, Anjia Wang, Giorgis Georgakoudis, Bronis R. de Supinski, Yonghong Yan, David Beckingsale, Todd Gamblin

Proceedings of the Accelerator Programming Using Directives - 8th International Workshop, 2021

Artemis: Automatic Runtime Tuning of Parallel Execution Parameters Using Machine Learning.

Chad Wood, Giorgis Georgakoudis, David Beckingsale, David Poliakoff, Alfredo Giménez, Kevin A. Huck, Allen D. Malony, Todd Gamblin

Proceedings of the High Performance Computing - 36th International Conference, 2021

A Holistic View of Memory Utilization on HPC Systems: Current and Future Trends.

Ivy Peng, Ian Karlin, Maya B. Gokhale, Kathleen Shoga, Matthew P. LeGendre, Todd Gamblin

Proceedings of the MEMSYS 2021: The International Symposium on Memory Systems, Washington, USA, September 27, 2021

2020

Scalable Comparative Visualization of Ensembles of Call Graphs.

Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma

CoRR, 2020

archspec: A library for detecting, labeling, and reasoning about microarchitectures.

Massimiliano Culpo, Gregory Becker, Carlos Eduardo Arango Gutierrez, Kenneth Hoste, Todd Gamblin

Proceedings of the 2nd International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC, 2020

Usability and Performance Improvements in Hatchet.

Stephanie Brink, Ian Lumsden, Connor Scully-Allison, Katy Williams, Olga Pearce, Todd Gamblin, Michela Taufer, Katherine E. Isaacs, Abhinav Bhatele

Proceedings of the IEEE/ACM International Workshop on HPC User Support Tools and Workshop on Programming and Performance Visualization Tools, 2020

Workflows are the New Applications: Challenges in Performance, Portability, and Productivity.

Tal Ben-Nun, Todd Gamblin, Daisy S. Hollman, Hari Krishnan, Chris J. Newburn

Proceedings of the IEEE/ACM International Workshop on Performance, 2020

CanarIO: Sounding the Alarm on IO-Related Performance Degradation.

Michael R. Wyatt II, Stephen Herbein, Kathleen Shoga, Todd Gamblin, Michela Taufer

Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

Auto-tuning Parameter Choices in HPC Applications using Bayesian Optimization.

Harshitha Menon, Abhinav Bhatele, Todd Gamblin

Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

CodeSeer: input-dependent code variants selection via machine learning.

Tao Wang, Nikhil Jain, David Böhme, David Beckingsale, Frank Mueller, Todd Gamblin

Proceedings of the ICS '20: 2020 International Conference on Supercomputing, 2020

2019

Preserving Command Line Workflow for a Package Management System Using ASCII DAG Visualization.

Katherine E. Isaacs, Todd Gamblin

IEEE Trans. Vis. Comput. Graph., 2019

Using Malleable Task Scheduling to Accelerate Package Manager Installations.

Samuel Knight, Jeremiah J. Wilke, Todd Gamblin

Proceedings of the Tools and Techniques for High Performance Computing, 2019

Preparation and optimization of a diverse workload for a large-scale heterogeneous system.

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

Proceedings of the International Conference for High Performance Computing, 2019

Hatchet: pruning the overgrowth in parallel profiles.

Abhinav Bhatele, Stephanie Brink, Todd Gamblin

Proceedings of the International Conference for High Performance Computing, 2019

Analyzing Cost-Performance Tradeoffs of HPC Network Designs under Different Constraints using Simulations.

Abhinav Bhatele, Nikhil Jain, Misbah Mubarak, Todd Gamblin

Proceedings of the 2019 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, 2019

FuncyTuner: Auto-tuning Scientific Applications With Per-loop Compilation.

Tao Wang, Nikhil Jain, David Beckingsale, David Böhme, Frank Mueller, Todd Gamblin

Proceedings of the 48th International Conference on Parallel Processing, 2019

2018

MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors.

Alfredo Giménez, Todd Gamblin, Ilir Jusufi, Abhinav Bhatele, Martin Schulz, Peer-Timo Bremer, Bernd Hamann

IEEE Trans. Vis. Comput. Graph., 2018

Autotuning in High-Performance Computing Applications.

Prasanna Balaprakash, Jack J. Dongarra, Todd Gamblin, Mary W. Hall, Jeffrey K. Hollingsworth, Boyana Norris, Richard W. Vuduc

Proc. IEEE, 2018

PADDLE: Performance Analysis Using a Data-Driven Learning Environment.

Jayaraman J. Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, Nikhil Jain, Tanzima Z. Islam, Abhinav Bhatele, Jae-Seung Yeom, Todd Gamblin

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

Bootstrapping Parameter Space Exploration for Fast Tuning.

Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin

Proceedings of the 32nd International Conference on Supercomputing, 2018

PRIONN: Predicting Runtime and IO using Neural Networks.

Michael R. Wyatt II, Stephen Herbein, Todd Gamblin, Adam Moody, Dong H. Ahn, Michela Taufer

Proceedings of the 47th International Conference on Parallel Processing, 2018

2017

xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit.

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

Supercomput. Front. Innov., 2017

Projecting Performance Data over Simulation Geometry Using SOSflow and ALPINE.

Chad Wood, Matthew Larsen, Alfredo Giménez, Kevin A. Huck, Cyrus Harrison, Todd Gamblin, Allen D. Malony

Proceedings of the Programming and Performance Visualization Tools, 2017

Performance modeling under resource constraints using deep transfer learning.

Aniruddha Marathe, Rushil Anirudh, Nikhil Jain, Abhinav Bhatele, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Jae-Seung Yeom, Barry Rountree, Todd Gamblin

Proceedings of the International Conference for High Performance Computing, 2017

Predicting the performance impact of different fat-tree configurations.

Nikhil Jain, Abhinav Bhatele, Louis H. Howell, David Böhme, Ian Karlin, Edgar A. León, Misbah Mubarak, Noah Wolfe, Todd Gamblin, Matthew L. Leininger

Proceedings of the International Conference for High Performance Computing, 2017

ScrubJay: deriving knowledge from the disarray of HPC performance data.

Alfredo Giménez, Todd Gamblin, Abhinav Bhatele, Chad Wood, Kathleen Shoga, Aniruddha Marathe, Peer-Timo Bremer, Bernd Hamann, Martin Schulz

Proceedings of the International Conference for High Performance Computing, 2017

DR-BW: Identifying Bandwidth Contention in NUMA Architectures with Supervised Learning.

Hao Xu, Shasha Wen, Alfredo Giménez, Todd Gamblin, Xu Liu

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017

Partitioning Low-Diameter Networks to Eliminate Inter-Job Interference.

Nikhil Jain, Abhinav Bhatele, Xiang Ni, Todd Gamblin, Laxmikant V. Kalé

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017

REPPAR Keynote.

Todd Gamblin

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium Workshops, 2017

Apollo: Reusable Models for Fast, Dynamic Tuning of Input-Dependent Code.

David Beckingsale, Olga Pearce, Ignacio Laguna, Todd Gamblin

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017

2016

Ordering Traces Logically to Identify Lateness in Message Passing Programs.

Katherine E. Isaacs, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann, Peer-Timo Bremer

IEEE Trans. Parallel Distributed Syst., 2016

Evaluating and extending user-level fault tolerance in MPI applications.

Ignacio Laguna, David F. Richards, Todd Gamblin, Martin Schulz, Bronis R. de Supinski, Kathryn M. Mohror, Howard Pritchard

Int. J. High Perform. Comput. Appl., 2016

A Scalable Observation System for Introspection and In Situ Analytics.

Chad Wood, Sudhanshu Sane, Daniel A. Ellsworth, Alfredo Giménez, Kevin A. Huck, Todd Gamblin, Allen D. Malony

Proceedings of the 5th Workshop on Extreme-Scale Programming Tools, 2016

VIPACT: A Visualization Interface for Analyzing Calling Context Trees.

Huu Tan Nguyen, Lai Wei, Abhinav Bhatele, Todd Gamblin, David Böhme, Martin Schulz, Kwan-Liu Ma, Peer-Timo Bremer

Proceedings of the Third Workshop on Visual Performance Analysis, 2016

Evaluating HPC networks via simulation of parallel workloads.

Nikhil Jain, Abhinav Bhatele, Sam White, Todd Gamblin, Laxmikant V. Kalé

Proceedings of the International Conference for High Performance Computing, 2016

A machine learning framework for performance coverage analysis of proxy applications.

Tanzima Z. Islam, Jayaraman J. Thiagarajan, Abhinav Bhatele, Martin Schulz, Todd Gamblin

Proceedings of the International Conference for High Performance Computing, 2016

Caliper: performance introspection for HPC software stacks.

David Böhme, Todd Gamblin, David Beckingsale, Peer-Timo Bremer, Alfredo Giménez, Matthew P. LeGendre, Olga Pearce, Martin Schulz

Proceedings of the International Conference for High Performance Computing, 2016

Managing Combinatorial Software Installations with Spack.

Gregory Becker, Peter Scheibel, Matthew P. LeGendre, Todd Gamblin

Proceedings of the 2016 Third International Workshop on HPC User Support Tools, 2016

A Study of Failures in Community Clusters: The Case of Conte.

Subrata Mitra, Suhas Javagal, Amiya Kumar Maji, Todd Gamblin, Adam Moody, Stephen Lien Harrell, Saurabh Bagchi

Proceedings of the 2016 IEEE International Symposium on Software Reliability Engineering Workshops, 2016

IPDRM Introduction and Committees.

Shuaiwen Leon Song, Todd Gamblin

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

MPMD Framework for Offloading Load Balance Computation.

Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Nancy M. Amato

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

VarSys Introduction.

Kirk W. Cameron, Todd Gamblin, Dimitrios S. Nikolopoulos

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Machine Learning Predictions of Runtime and IO Traffic on High-End Clusters.

Ryan McKenna, Stephen Herbein, Adam Moody, Todd Gamblin, Michela Taufer

Proceedings of the 2016 IEEE International Conference on Cluster Computing, 2016

2015

Diagnosis of Performance Faults in LargeScale MPI Applications via Probabilistic Progress-Dependence Inference.

Ignacio Laguna, Dong H. Ahn, Bronis R. de Supinski, Saurabh Bagchi, Todd Gamblin

IEEE Trans. Parallel Distributed Syst., 2015

Connecting Performance Analysis and Visualization (Dagstuhl Perspectives Workshop 14022).

Peer-Timo Bremer, Bernd Mohr, Valerio Pascucci, Martin Schulz, Todd Gamblin, Holger Brunst

Dagstuhl Manifestos, 2015

Debugging high-performance computing applications at massive scales.

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

Commun. ACM, 2015

Recovering logical structure from Charm++ event traces.

Katherine E. Isaacs, Abhinav Bhatele, Jonathan Lifflander, David Böhme, Todd Gamblin, Martin Schulz, Bernd Hamann, Peer-Timo Bremer

Proceedings of the International Conference for High Performance Computing, 2015

Relating memory performance data to application domain data using an integration API.

Benafsh Husain, Alfredo Giménez, Joshua A. Levine, Todd Gamblin, Peer-Timo Bremer

Proceedings of the 2nd Workshop on Visual Performance Analysis, 2015

The Spack package manager: bringing order to HPC software chaos.

Todd Gamblin, Matthew P. LeGendre, Michael R. Collette, Gregory L. Lee, Adam Moody, Bronis R. de Supinski, Scott Futral

Proceedings of the International Conference for High Performance Computing, 2015

Decoupled load balancing.

Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Nancy M. Amato

Proceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2015

Identifying the Culprits Behind Network Congestion.

Abhinav Bhatele, Andrew R. Titus, Jayaraman J. Thiagarajan, Nikhil Jain, Todd Gamblin, Peer-Timo Bremer, Martin Schulz, Laxmikant V. Kalé

Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium, 2015

2014

Combing the Communication Hairball: Visualizing Parallel Execution Traces using Logical Time.

Katherine E. Isaacs, Peer-Timo Bremer, Ilir Jusufi, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann

IEEE Trans. Vis. Comput. Graph., 2014

State of the Art of Performance Visualization.

Katherine E. Isaacs, Alfredo Giménez, Ilir Jusufi, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann, Peer-Timo Bremer

Proceedings of the 16th Eurographics Conference on Visualization, 2014

Dissecting On-Node Memory Access Performance: A Semantic Approach.

Alfredo Giménez, Todd Gamblin, Barry Rountree, Abhinav Bhatele, Ilir Jusufi, Peer-Timo Bremer, Bernd Hamann

Proceedings of the International Conference for High Performance Computing, 2014

Evaluating User-Level Fault Tolerance for MPI Applications.

Ignacio Laguna, David F. Richards, Todd Gamblin, Martin Schulz, Bronis R. de Supinski

Proceedings of the 21st European MPI Users' Group Meeting, 2014

Extracting logical structure and identifying stragglers in parallel execution traces.

Katherine E. Isaacs, Todd Gamblin, Abhinav Bhatele, Peer-Timo Bremer, Martin Schulz, Bernd Hamann

Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2014

Accurate application progress analysis for large-scale parallel debugging.

Subrata Mitra, Ignacio Laguna, Dong H. Ahn, Saurabh Bagchi, Martin Schulz, Todd Gamblin

Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation, 2014

FMI: Fault Tolerant Messaging Interface for Fast and Transparent Recovery.

Kento Sato, Adam Moody, Kathryn M. Mohror, Todd Gamblin, Bronis R. de Supinski, Naoya Maruyama, Satoshi Matsuoka

Proceedings of the 2014 IEEE 28th International Parallel and Distributed Processing Symposium, 2014

Load balancing n-body simulations with highly non-uniform density.

Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Tom Arsenlis, Nancy M. Amato

Proceedings of the 2014 International Conference on Supercomputing, 2014

Optimizing the performance of parallel applications on a 5D torus via task mapping.

Abhinav Bhatele, Nikhil Jain, Katherine E. Isaacs, Ronak Buch, Todd Gamblin, Steven H. Langer, Laxmikant V. Kalé

Proceedings of the 21st International Conference on High Performance Computing, 2014

A User-Level InfiniBand-Based File System and Checkpoint Strategy for Burst Buffers.

Kento Sato, Kathryn M. Mohror, Adam Moody, Todd Gamblin, Bronis R. de Supinski, Naoya Maruyama, Satoshi Matsuoka

Proceedings of the 14th IEEE/ACM International Symposium on Cluster, 2014

2013

Parallelizing heavyweight debugging tools with mpiecho.

Barry Rountree, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, David K. Lowenthal, Guy Cobb, Henry M. Tufo

Parallel Comput., 2013

Trellis: Portability across architectures with a high-level framework.

Lukasz G. Szafaryn, Todd Gamblin, Bronis R. de Supinski, Kevin Skadron

J. Parallel Distributed Comput., 2013

Predicting application performance using supervised learning on communication features.

Nikhil Jain, Abhinav Bhatele, Michael P. Robson, Todd Gamblin, Laxmikant V. Kalé

Proceedings of the International Conference for High Performance Computing, 2013

Performance Analysis Techniques for the Exascale Co-Design Process.

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

Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013

Efficient and Scalable Retrieval Techniques for Global File Properties.

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

Proceedings of the 27th IEEE International Symposium on Parallel and Distributed Processing, 2013

Massively parallel loading.

Wolfgang Frings, Dong H. Ahn, Matthew P. LeGendre, Todd Gamblin, Bronis R. de Supinski, Felix Wolf

Proceedings of the International Conference on Supercomputing, 2013

2012

Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations.

Aaditya G. Landge, Joshua A. Levine, Abhinav Bhatele, Katherine E. Isaacs, Todd Gamblin, Martin Schulz, Steve H. Langer, Peer-Timo Bremer, Valerio Pascucci

IEEE Trans. Vis. Comput. Graph., 2012

Memory Trace Compression and Replay for SPMD Systems Using Extended PRSDs.

Sandeep Budanur, Frank Mueller, Todd Gamblin

Comput. J., 2012

Design and modeling of a non-blocking checkpointing system.

Kento Sato, Naoya Maruyama, Kathryn M. Mohror, Adam Moody, Todd Gamblin, Bronis R. de Supinski, Satoshi Matsuoka

Proceedings of the SC Conference on High Performance Computing Networking, 2012

Abstract: Slack-Conscious Lightweight Loop Scheduling for Improving Scalability of Bulk-synchronous MPI Applications.

Vivek Kale, Todd Gamblin, Torsten Hoefler, Bronis R. de Supinski, William D. Gropp

Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Abstract: Exploring Performance Data with Boxfish.

Katherine E. Isaacs, Aaditya G. Landge, Todd Gamblin, Peer-Timo Bremer, Valerio Pascucci, Bernd Hamann

Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Mapping applications with collectives over sub-communicators on torus networks.

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

Proceedings of the SC Conference on High Performance Computing Networking, 2012

Novel views of performance data to analyze large-scale adaptive applications.

Abhinav Bhatele, Todd Gamblin, Katherine E. Isaacs, Brian T. N. Gunney, Martin Schulz, Peer-Timo Bremer, Bernd Hamann

Proceedings of the SC Conference on High Performance Computing Networking, 2012

Poster: Evaluation Topology Mapping via Graph Partitioning.

Anshu Arya, Todd Gamblin, Bronis R. de Supinski, Laxmikant V. Kalé

Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Abstract: Evaluating Topology Mapping via Graph Partitioning.

Anshu Arya, Todd Gamblin, Bronis R. de Supinski, Laxmikant V. Kalé

Proceedings of the 2012 SC Companion: High Performance Computing, 2012

The myrmics memory allocator: hierarchical, message-passing allocation for global address spaces.

Spyros Lyberis, Polyvios Pratikakis, Dimitrios S. Nikolopoulos, Martin Schulz, Todd Gamblin, Bronis R. de Supinski

Proceedings of the International Symposium on Memory Management, 2012

Quantifying the effectiveness of load balance algorithms.

Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Nancy M. Amato

Proceedings of the International Conference on Supercomputing, 2012

Probabilistic diagnosis of performance faults in large-scale parallel applications.

Ignacio Laguna, Dong H. Ahn, Bronis R. de Supinski, Saurabh Bagchi, Todd Gamblin

Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2012

2011

Large scale debugging of parallel tasks with AutomaDeD.

Ignacio Laguna, Todd Gamblin, Bronis R. de Supinski, Saurabh Bagchi, Greg Bronevetsky, Dong H. Ahn, Martin Schulz, Barry Rountree

Proceedings of the Conference on High Performance Computing Networking, 2011

Creating a Tool Set for Optimizing Topology-Aware Node Mappings.

Martin Schulz, Abhinav Bhatele, Peer-Timo Bremer, Todd Gamblin, Katherine E. Isaacs, Joshua A. Levine, Valerio Pascucci

Proceedings of the Tools for High Performance Computing 2011, 2011

Reconciling Sampling and Direct Instrumentation for Unintrusive Call-Path Profiling of MPI Programs.

Zoltán Szebenyi, Todd Gamblin, Martin Schulz, Bronis R. de Supinski, Felix Wolf, Brian J. N. Wylie

Proceedings of the 25th IEEE International Symposium on Parallel and Distributed Processing, 2011

Challenges of Scaling Algebraic Multigrid Across Modern Multicore Architectures.

Allison H. Baker, Todd Gamblin, Martin Schulz, Ulrike Meier Yang

Proceedings of the 25th IEEE International Symposium on Parallel and Distributed Processing, 2011

Interpreting Performance Data across Intuitive Domains.

Martin Schulz, Joshua A. Levine, Peer-Timo Bremer, Todd Gamblin, Valerio Pascucci

Proceedings of the International Conference on Parallel Processing, 2011

2010

ScalaTrace: Tracing, Analysis and Modeling of HPC Codes at Scale.

Frank Mueller, Xing Wu, Martin Schulz, Bronis R. de Supinski, Todd Gamblin

Proceedings of the Applied Parallel and Scientific Computing, 2010

Clustering performance data efficiently at massive scales.

Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Robert J. Fowler, Daniel A. Reed

Proceedings of the 24th International Conference on Supercomputing, 2010

Scaling Algebraic Multigrid Solvers: On the Road to Exascale.

Allison H. Baker, Robert D. Falgout, Todd Gamblin, Tzanio V. Kolev, Martin Schulz, Ulrike Meier Yang

Proceedings of the Competence in High Performance Computing 2010, 2010

2009

Scalable performance measurement and analysis.

Todd Gamblin

PhD thesis, 2009

2008

Scalable load-balance measurement for SPMD codes.

Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Robert J. Fowler, Daniel A. Reed

Proceedings of the ACM/IEEE Conference on High Performance Computing, 2008

Scalable methods for monitoring and detecting behavioral equivalence classes in scientific codes.

Todd Gamblin, Robert J. Fowler, Daniel A. Reed

Proceedings of the 22nd IEEE International Symposium on Parallel and Distributed Processing, 2008

2006

Challenges of Scale: When All Computing Becomes Grid Computing.

Robert J. Fowler, Todd Gamblin, Gopi Kandaswamy, Anirban Mandal, Allan Porterfield, Lavanya Ramakrishnan, Daniel A. Reed

Proceedings of the High Performance Computing and Grids in Action, 2006