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 (High Performance Computing Workshop, 2006)

Scalable methods for monitoring and detecting behavioral equivalence classes in scientific codes. - Todd Gamblin; Robert J. Fowler; Daniel A. Reed (IPDPS, 2008)

Scalable load-balance measurement for SPMD codes. - Todd Gamblin; Bronis R. de Supinski; Martin Schulz 001; Robert J. Fowler; Daniel A. Reed (SC, 2008)

Scalable performance measurement and analysis. - Todd Gamblin (2009)

Scaling Algebraic Multigrid Solvers: On the Road to Exascale. - Allison H. Baker; Robert D. Falgout; Todd Gamblin; Tzanio V. Kolev; Martin Schulz 001; Ulrike Meier Yang (CHPC, 2010)

Clustering performance data efficiently at massive scales. - Todd Gamblin; Bronis R. de Supinski; Martin Schulz 001; Robert J. Fowler; Daniel A. Reed (ICS, 2010)

ScalaTrace: Tracing, Analysis and Modeling of HPC Codes at Scale. - Frank Mueller 001; Xing Wu 004; Martin Schulz 001; Bronis R. de Supinski; Todd Gamblin (PARA (2), 2010)

Interpreting Performance Data across Intuitive Domains. - Martin Schulz 001; Joshua A. Levine; Peer-Timo Bremer; Todd Gamblin; Valerio Pascucci (ICPP, 2011)

Challenges of Scaling Algebraic Multigrid Across Modern Multicore Architectures. - Allison H. Baker; Todd Gamblin; Martin Schulz 001; Ulrike Meier Yang (IPDPS, 2011)

Reconciling Sampling and Direct Instrumentation for Unintrusive Call-Path Profiling of MPI Programs. - Zoltán Szebenyi; Todd Gamblin; Martin Schulz 001; Bronis R. de Supinski; Felix Wolf 001; Brian J. N. Wylie (IPDPS, 2011)

Creating a Tool Set for Optimizing Topology-Aware Node Mappings. - Martin Schulz 001; Abhinav Bhatele; Peer-Timo Bremer; Todd Gamblin; Katherine E. Isaacs; Joshua A. Levine; Valerio Pascucci (Parallel Tools Workshop, 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 001; Barry Rountree (SC, 2011)

Probabilistic diagnosis of performance faults in large-scale parallel applications. - Ignacio Laguna; Dong H. Ahn; Bronis R. de Supinski; Saurabh Bagchi; Todd Gamblin (PACT, 2012)

Quantifying the effectiveness of load balance algorithms. - Olga Pearce; Todd Gamblin; Bronis R. de Supinski; Martin Schulz 001; Nancy M. Amato (ICS, 2012)

The myrmics memory allocator: hierarchical, message-passing allocation for global address spaces. - Spyros Lyberis; Polyvios Pratikakis; Dimitrios S. Nikolopoulos; Martin Schulz 001; Todd Gamblin; Bronis R. de Supinski (ISMM, 2012)

Abstract: Evaluating Topology Mapping via Graph Partitioning. - Anshu Arya; Todd Gamblin; Bronis R. de Supinski; Laxmikant V. Kalé (SC Companion, 2012)

Poster: Evaluation Topology Mapping via Graph Partitioning. - Anshu Arya; Todd Gamblin; Bronis R. de Supinski; Laxmikant V. Kalé (SC Companion, 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 001; Peer-Timo Bremer; Bernd Hamann (SC, 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 001; Charles H. Still (SC, 2012)

Abstract: Exploring Performance Data with Boxfish. - Katherine E. Isaacs; Aaditya G. Landge; Todd Gamblin; Peer-Timo Bremer; Valerio Pascucci; Bernd Hamann (SC Companion, 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 (SC Companion, 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 (SC, 2012)

Memory Trace Compression and Replay for SPMD Systems Using Extended PRSDs. - Sandeep Budanur; Frank Mueller 001; Todd Gamblin (Comput. J., 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 001; Steve H. Langer; Peer-Timo Bremer; Valerio Pascucci (IEEE Trans. Vis. Comput. Graph., 2012)

Massively parallel loading. - Wolfgang Frings; Dong H. Ahn; Matthew P. LeGendre; Todd Gamblin; Bronis R. de Supinski; Felix Wolf 001 (ICS, 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 001 (IPDPS, 2013)

Performance Analysis Techniques for the Exascale Co-Design Process. - Martin Schulz 001; 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; et al. (PARCO, 2013)

Predicting application performance using supervised learning on communication features. - Nikhil Jain; Abhinav Bhatele; Michael P. Robson; Todd Gamblin; Laxmikant V. Kalé (SC, 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)

Parallelizing heavyweight debugging tools with mpiecho. - Barry Rountree; Todd Gamblin; Bronis R. de Supinski; Martin Schulz 001; David K. Lowenthal; Guy Cobb; Henry M. Tufo (Parallel Comput., 2013)

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 (CCGRID, 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 (HiPC, 2014)

Load balancing n-body simulations with highly non-uniform density. - Olga Pearce; Todd Gamblin; Bronis R. de Supinski; Tom Arsenlis; Nancy M. Amato (ICS, 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 (IPDPS, 2014)

Accurate application progress analysis for large-scale parallel debugging. - Subrata Mitra; Ignacio Laguna; Dong H. Ahn; Saurabh Bagchi; Martin Schulz 001; Todd Gamblin (PLDI, 2014)

Extracting logical structure and identifying stragglers in parallel execution traces. - Katherine E. Isaacs; Todd Gamblin; Abhinav Bhatele; Peer-Timo Bremer; Martin Schulz 001; Bernd Hamann (PPoPP, 2014)

Evaluating User-Level Fault Tolerance for MPI Applications. - Ignacio Laguna; David F. Richards; Todd Gamblin; Martin Schulz 001; Bronis R. de Supinski (EuroMPI/ASIA, 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 (SC, 2014)

State of the Art of Performance Visualization. - Katherine E. Isaacs; Alfredo Giménez; Ilir Jusufi; Todd Gamblin; Abhinav Bhatele; Martin Schulz 001; Bernd Hamann; Peer-Timo Bremer (EuroVis (STARs), 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 001; Bernd Hamann (IEEE Trans. Vis. Comput. Graph., 2014)

Identifying the Culprits Behind Network Congestion. - Abhinav Bhatele; Andrew R. Titus; Jayaraman J. Thiagarajan; Nikhil Jain; Todd Gamblin; Peer-Timo Bremer; Martin Schulz 001; Laxmikant V. Kalé (IPDPS, 2015)

Decoupled load balancing. - Olga Pearce; Todd Gamblin; Bronis R. de Supinski; Martin Schulz 001; Nancy M. Amato (PPoPP, 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 (SC, 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 (VPA@SC, 2015)

Recovering logical structure from Charm++ event traces. - Katherine E. Isaacs; Abhinav Bhatele; Jonathan Lifflander; David Böhme; Todd Gamblin; Martin Schulz 001; Bernd Hamann; Peer-Timo Bremer (SC, 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 001; Saurabh Bagchi; Milind Kulkarni 001; Bowen Zhou 008; Zhezhe Chen; Feng Qin (Commun. ACM, 2015)

Connecting Performance Analysis and Visualization (Dagstuhl Perspectives Workshop 14022). - Peer-Timo Bremer; Bernd Mohr; Valerio Pascucci; Martin Schulz 001; Todd Gamblin; Holger Brunst (Dagstuhl Manifestos, 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)

Machine Learning Predictions of Runtime and IO Traffic on High-End Clusters. - Ryan McKenna; Stephen Herbein; Adam Moody; Todd Gamblin; Michela Taufer (CLUSTER, 2016)

VarSys Introduction. - Kirk W. Cameron; Todd Gamblin; Dimitrios S. Nikolopoulos (IPDPS Workshops, 2016)

MPMD Framework for Offloading Load Balance Computation. - Olga Pearce; Todd Gamblin; Bronis R. de Supinski; Martin Schulz 001; Nancy M. Amato (IPDPS, 2016)

IPDRM Introduction and Committees. - Shuaiwen Leon Song; Todd Gamblin (IPDPS Workshops, 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 (ISSRE Workshops, 2016)

Managing Combinatorial Software Installations with Spack. - Gregory Becker; Peter Scheibel; Matthew P. LeGendre; Todd Gamblin (HUST@SC, 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 001 (SC, 2016)

A machine learning framework for performance coverage analysis of proxy applications. - Tanzima Z. Islam; Jayaraman J. Thiagarajan; Abhinav Bhatele; Martin Schulz 001; Todd Gamblin (SC, 2016)

Evaluating HPC networks via simulation of parallel workloads. - Nikhil Jain; Abhinav Bhatele; Sam White; Todd Gamblin; Laxmikant V. Kalé (SC, 2016)

VIPACT: A Visualization Interface for Analyzing Calling Context Trees. - Huu Tan Nguyen; Lai Wei; Abhinav Bhatele; Todd Gamblin; David Böhme; Martin Schulz 001; Kwan-Liu Ma; Peer-Timo Bremer (VPA@SC, 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 (ESPT@SC, 2016)

Evaluating and extending user-level fault tolerance in MPI applications. - Ignacio Laguna; David F. Richards; Todd Gamblin; Martin Schulz 001; Bronis R. de Supinski; Kathryn M. Mohror; Howard Pritchard (Int. J. High Perform. Comput. Appl., 2016)

Ordering Traces Logically to Identify Lateness in Message Passing Programs. - Katherine E. Isaacs; Todd Gamblin; Abhinav Bhatele; Martin Schulz 001; Bernd Hamann; Peer-Timo Bremer (IEEE Trans. Parallel Distributed Syst., 2016)

Apollo: Reusable Models for Fast, Dynamic Tuning of Input-Dependent Code. - David Beckingsale; Olga Pearce; Ignacio Laguna; Todd Gamblin (IPDPS, 2017)

REPPAR Keynote. - Todd Gamblin (IPDPS Workshops, 2017)

Partitioning Low-Diameter Networks to Eliminate Inter-Job Interference. - Nikhil Jain; Abhinav Bhatele; Xiang Ni; Todd Gamblin; Laxmikant V. Kalé (IPDPS, 2017)

DR-BW: Identifying Bandwidth Contention in NUMA Architectures with Supervised Learning. - Hao Xu 048; Shasha Wen; Alfredo Giménez; Todd Gamblin; Xu Liu 001 (IPDPS, 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 001 (SC, 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 (SC, 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 (SC, 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 (ESPT/VPA@SC, 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; et al. (Supercomput. Front. Innov., 2017)

PRIONN: Predicting Runtime and IO using Neural Networks. - Michael R. Wyatt II; Stephen Herbein; Todd Gamblin; Adam Moody; Dong H. Ahn; Michela Taufer (ICPP, 2018)

Bootstrapping Parameter Space Exploration for Fast Tuning. - Jayaraman J. Thiagarajan; Nikhil Jain; Rushil Anirudh; Alfredo Giménez; Rahul Sridhar; Aniruddha Marathe; Tao Wang 077; Murali Emani; Abhinav Bhatele; Todd Gamblin (ICS, 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 (IPDPS, 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)

MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors. - Alfredo Giménez; Todd Gamblin; Ilir Jusufi; Abhinav Bhatele; Martin Schulz 001; Peer-Timo Bremer; Bernd Hamann (IEEE Trans. Vis. Comput. Graph., 2018)

FuncyTuner: Auto-tuning Scientific Applications With Per-loop Compilation. - Tao Wang 077; Nikhil Jain; David Beckingsale; David Böhme; Frank Mueller 001; Todd Gamblin (ICPP, 2019)

Analyzing Cost-Performance Tradeoffs of HPC Network Designs under Different Constraints using Simulations. - Abhinav Bhatele; Nikhil Jain; Misbah Mubarak; Todd Gamblin (SIGSIM-PADS, 2019)

Hatchet: pruning the overgrowth in parallel profiles. - Abhinav Bhatele; Stephanie Brink; Todd Gamblin (SC, 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 001; Guojing Cong; Carlos H. A. Costa; Johann Dahm; Giacomo Domeniconi; et al. (SC, 2019)

Using Malleable Task Scheduling to Accelerate Package Manager Installations. - Samuel Knight; Jeremiah J. Wilke; Todd Gamblin (HUST/SE-HER/WIHPC@SC, 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)

CodeSeer: input-dependent code variants selection via machine learning. - Tao Wang 077; Nikhil Jain; David Böhme; David Beckingsale; Frank Mueller 001; Todd Gamblin (ICS, 2020)

Auto-tuning Parameter Choices in HPC Applications using Bayesian Optimization. - Harshitha Menon; Abhinav Bhatele; Todd Gamblin (IPDPS, 2020)

CanarIO: Sounding the Alarm on IO-Related Performance Degradation. - Michael R. Wyatt II; Stephen Herbein; Kathleen Shoga; Todd Gamblin; Michela Taufer (IPDPS, 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 (P3HPC@SC, 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 (HUST/ProTools@SC, 2020)

archspec: A library for detecting, labeling, and reasoning about microarchitectures. - Massimiliano Culpo; Gregory Becker; Carlos Eduardo Arango Gutierrez; Kenneth Hoste; Todd Gamblin (CANOPIE-HPC@SC, 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)

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 (MEMSYS, 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 (ISC, 2021)

Extending OpenMP for Machine Learning-Driven Adaptation. - Chunhua Liao; Anjia Wang; Giorgis Georgakoudis; Bronis R. de Supinski; Yonghong Yan 001; David Beckingsale; Todd Gamblin (WACCPD@SC, 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)

Resource Utilization Aware Job Scheduling to Mitigate Performance Variability. - Daniel Nichols; Aniruddha Marathe; Kathleen Shoga; Todd Gamblin; Abhinav Bhatele (IPDPS, 2022)

Searching for High-Fidelity Builds Using Active Learning. - Harshitha Menon; Konstantinos Parasyris; Tom Scogland; Todd Gamblin (MSR, 2022)

Using Answer Set Programming for HPC Dependency Solving. - Todd Gamblin; Massimiliano Culpo; Gregory Becker; Sergei Shudler (SC, 2022)

Mapping Out the HPC Dependency Chaos. - Farid Zakaria; Thomas R. W. Scogland; Todd Gamblin; Carlos Maltzahn (SC, 2022)

Reliabuild: Searching for High-Fidelity Builds Using Active Learning. - Harshitha Menon; Konstantinos Parasyris; Tom Scogland; Todd Gamblin (CoRR, 2022)

Using Solver-Aided Languages to Build Package Managers. - Donald Pinckney; Arjun Guha; Massimiliano Culpo; Todd Gamblin (CoRR, 2022)

Overcoming Challenges to Continuous Integration in HPC. - Todd Gamblin; Daniel S. Katz (Comput. Sci. Eng., 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)

Flexible and Optimal Dependency Management via Max-SMT. - Donald Pinckney; Federico Cassano; Arjun Guha; Jonathan Bell 001; Massimiliano Culpo; Todd Gamblin (ICSE, 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 (SC Workshops, 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)

Modeling Parallel Programs using Large Language Models. - Daniel Nichols; Aniruddha Marathe; Harshitha Menon; Todd Gamblin; Abhinav Bhatele (CoRR, 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., 2023)

An Exploration of Global Optimization Strategies for Autotuning OpenMP-based Codes. - Gregory Bolet; Giorgis Georgakoudis; Konstantinos Parasyris; Kirk W. Cameron; David Beckingsale; Todd Gamblin (IPDPS (Workshops), 2024)

Learning to Predict and Improve Build Successes in Package Ecosystems. - Harshitha Menon; Daniel Nichols; Abhinav Bhatele; Todd Gamblin (MSR, 2024)

A Probabilistic Approach To Selecting Build Configurations in Package Managers. - Daniel Nichols; Harshitha Menon; Todd Gamblin; Abhinav Bhatele (SC, 2024)

HPC-Coder: Modeling Parallel Programs using Large Language Models. - Daniel Nichols; Aniruddha Marathe; Harshitha Menon; Todd Gamblin; Abhinav Bhatele (ISC, 2024)

Performance-Aligned LLMs for Generating Fast Code. - Daniel Nichols; Pranav Polasam; Harshitha Menon; Aniruddha Marathe; Todd Gamblin; Abhinav Bhatele (CoRR, 2024)

Toward a Cohesive AI and Simulation Software Ecosystem for Scientific Innovation. - Michael A. Heroux; Sameer Shende; Lois Curfman McInnes; Todd Gamblin; James M. Willenbring (CoRR, 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)

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, 2024)

Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions. - Keita Teranishi; Harshitha Menon; William F. Godoy; Prasanna Balaprakash; David Bau; Tal Ben-Nun; Abhinav Bhatele; Franz Franchetti; Michael E. Franusich; Todd Gamblin; Giorgis Georgakoudis; Tom Goldstein; et al. (CoRR, 2025)