Ian Karlin

According to our database, Ian Karlin authored at least 40 papers between 2008 and 2024.

Collaborative distances:

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

2024

Heterogeneous computing in a strongly-connected CPU-GPU environment: fast multiple time-evolution equation-based modeling accelerated using data-driven approach.

Tsuyoshi Ichimura, Kohei Fujita, Muneo Hori, Lalith Maddegedara, Jack C. Wells, Alan Gray, Ian Karlin, John Linford

CoRR, 2024

2022

Understanding Power and Energy Utilization in Large Scale Production Physics Simulation Codes.

Brian S. Ryujin, Arturo Vargas, Ian Karlin, Shawn A. Dawson, Kenneth Weiss, Adam Bertsch, Michael Scott McKinley, Michael R. Collette, Simon D. Hammond, Kevin T. Pedretti, Robert N. Rieben

CoRR, 2022

Scalable Composition and Analysis Techniques for Massive Scientific Workflows.

Dong H. Ahn, Xiaohua Zhang, Jeffrey Mast, Stephen Herbein, Francesco Di Natale, Dan Kirshner, Sam Ade Jacobs, Ian Karlin, Daniel J. Milroy, Bronis R. de Supinski, Brian Van Essen, Jonathan E. Allen, Felice C. Lightstone

Proceedings of the 18th IEEE International Conference on e-Science, 2022

2021

Efficient exascale discretizations: High-order finite element methods.

Tzanio V. Kolev, Paul F. Fischer, Misun Min, Jack J. Dongarra, Jed Brown, Veselin Dobrev, Tim Warburton, Stanimire Tomov, Mark S. Shephard, Ahmad Abdelfattah, Valeria Barra, Natalie Beams, Jean-Sylvain Camier, Noel Chalmers, Yohann Dudouit, Ali Karakus, Ian Karlin, Stefan Kerkemeier, Yu-Hsiang Lan, David S. Medina, Elia Merzari, Aleksandr Obabko, Will Pazner, Thilina Rathnayake, Cameron W. Smith, Lukas Spies, Kasia Swirydowicz, Jeremy L. Thompson, Ananias Tomboulides, Vladimir Z. Tomov

Int. J. High Perform. Comput. Appl., 2021

Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models.

Sam Ade Jacobs, Tim Moon, Kevin McLoughlin, Derek Jones, David Hysom, Dong H. Ahn, John C. Gyllenhaal, Pythagoras Watson, Felice C. Lightstone, Jonathan E. Allen, Ian Karlin, Brian Van Essen

Int. J. High Perform. Comput. Appl., 2021

Is Disaggregation possible for HPC Cognitive Simulation?

Michael R. Wyatt II, Valen Yamamoto, Zoë Tosi, Ian Karlin, Brian Van Essen

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 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

Monitoring Large Scale Supercomputers: A Case Study with the Lassen Supercomputer.

Tapasya Patki, Adam Bertsch, Ian Karlin, Dong H. Ahn, Brian Van Essen, Barry Rountree, Bronis R. de Supinski, Nathan Besaw

Proceedings of the IEEE International Conference on Cluster Computing, 2021

On-the-Fly, Robust Translation of MPI Libraries.

Edgar A. León, Marc Joos, Nathan Hanford, Adrien Cotte, Tony Delforge, François Diakhaté, Vincent Ducrot, Ian Karlin, Marc Pérache

Proceedings of the IEEE International Conference on Cluster Computing, 2021

2020

Sierra Center of Excellence: Lessons learned.

Johann Dahm, David F. Richards, Aaron Black, Adam Bertsch, Leopold Grinberg, Ian Karlin, Sara Kokkila Schumacher, Edgar A. León, Rob Neely, Ramesh Pankajakshan, Olga Pearce

IBM J. Res. Dev., 2020

TOSS-2020: a commodity software stack for HPC.

Edgar A. León, Trent D'Hooge, Nathan Hanford, Ian Karlin, Ramesh Pankajakshan, Jim Foraker, Chris Chambreau, Matthew L. Leininger

Proceedings of the International Conference for High Performance Computing, 2020

Challenges of GPU-aware Communication in MPI.

Nathan Hanford, Ramesh Pankajakshan, Edgar A. León, Ian Karlin

Proceedings of the Workshop on Exascale MPI, 2020

2019

An evaluation of the CORAL interconnects.

Christopher Zimmer, Scott Atchley, Ramesh Pankajakshan, Brian E. Smith, Ian Karlin, Matthew L. Leininger, Adam Bertsch, Brian S. Ryujin, Jason Burmark, André Walker-Loud, Michael A. Clark, Olga Pearce

Proceedings of the International Conference for High Performance Computing, 2019

Testing the Limits of Tapered Fat Tree Networks.

Philip Taffet, Sanil Rao, Edgar A. León, Ian Karlin

Proceedings of the 2019 IEEE/ACM Performance Modeling, 2019

Exploring Regression of Data Race Detection Tools Using DataRaceBench.

Pei-Hung Lin, Chunhua Liao, Markus Schordan, Ian Karlin

Proceedings of the 2019 IEEE/ACM 3rd International Workshop on Software Correctness for HPC Applications (Correctness), 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

2018

Using Polyhedral Analysis to Verify OpenMP Applications are Data Race Free.

Fangke Ye, Markus Schordan, Chunhua Liao, Pei-Hung Lin, Ian Karlin, Vivek Sarkar

Proceedings of the 2nd IEEE/ACM International Workshop on Software Correctness for HPC Applications, 2018

The design, deployment, and evaluation of the CORAL pre-exascale systems.

Sudharshan S. Vazhkudai, Bronis R. de Supinski, Arthur S. Bland, Al Geist, James C. Sexton, Jim Kahle, Christopher Zimmer, Scott Atchley, Sarp Oral, Don E. Maxwell, Verónica G. Vergara Larrea, Adam Bertsch, Robin Goldstone, Wayne Joubert, Chris Chambreau, David Appelhans, Robert Blackmore, Ben Casses, George Chochia, Gene Davison, Matthew A. Ezell, Tom Gooding, Elsa Gonsiorowski, Leopold Grinberg, Bill Hanson, Bill Hartner, Ian Karlin, Matthew L. Leininger, Dustin Leverman, Chris Marroquin, Adam Moody, Martin Ohmacht, Ramesh Pankajakshan, Fernando Pizzano, James H. Rogers, Bryan S. Rosenburg, Drew Schmidt, Mallikarjun Shankar, Feiyi Wang, Py Watson, Bob Walkup, Lance D. Weems, Junqi Yin

Proceedings of the International Conference for High Performance Computing, 2018

A Semantics-Driven Approach to Improving DataRaceBench's OpenMP Standard Coverage.

Chunhua Liao, Pei-Hung Lin, Markus Schordan, Ian Karlin

Proceedings of the Evolving OpenMP for Evolving Architectures, 2018

Runtime and Memory Evaluation of Data Race Detection Tools.

Pei-Hung Lin, Chunhua Liao, Markus Schordan, Ian Karlin

Proceedings of the Leveraging Applications of Formal Methods, Verification and Validation. Verification, 2018

2017

DataRaceBench: a benchmark suite for systematic evaluation of data race detection tools.

Chunhua Liao, Pei-Hung Lin, Joshua Asplund, Markus Schordan, Ian Karlin

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

2016

Program optimizations: The interplay between power, performance, and energy.

Edgar A. León, Ian Karlin, Ryan E. Grant, Matthew G. F. Dosanjh

Parallel Comput., 2016

Characterizing parallel scientific applications on commodity clusters: an empirical study of a tapered fat-tree.

Edgar A. León, Ian Karlin, Abhinav Bhatele, Steven H. Langer, Chris Chambreau, Louis H. Howell, Trent D'Hooge, Matthew L. Leininger

Proceedings of the International Conference for High Performance Computing, 2016

Early Experiences Porting Three Applications to OpenMP 4.5.

Ian Karlin, Tom Scogland, Arpith C. Jacob, Samuel F. Antão, Gheorghe-Teodor Bercea, Carlo Bertolli, Bronis R. de Supinski, Erik W. Draeger, Alexandre E. Eichenberger, Jim Glosli, Holger Jones, Adam Kunen, David Poliakoff, David F. Richards

Proceedings of the OpenMP: Memory, Devices, and Tasks, 2016

System Noise Revisited: Enabling Application Scalability and Reproducibility with SMT.

Edgar A. León, Ian Karlin, Adam Moody

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

High-Performance Tensor Contractions for GPUs.

Ahmad Abdelfattah, Marc Baboulin, Veselin Dobrev, Jack J. Dongarra, Christopher W. Earl, Joel Falcou, Azzam Haidar, Ian Karlin, Tzanio V. Kolev, Ian Masliah, Stanimire Tomov

Proceedings of the International Conference on Computational Science 2016, 2016

Fast Multi-parameter Performance Modeling.

Alexandru Calotoiu, David Beckingsale, Christopher W. Earl, Torsten Hoefler, Ian Karlin, Martin Schulz, Felix Wolf

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

2015

Data Layout Optimization for Portable Performance.

Kamal Sharma, Ian Karlin, Jeff Keasler, James R. McGraw, Vivek Sarkar

Proceedings of the Euro-Par 2015: Parallel Processing, 2015

Optimizing Explicit Hydrodynamics for Power, Energy, and Performance.

Edgar A. León, Ian Karlin, Ryan E. Grant

Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015

2014

Performance Characteristics of HYDRA - A Multi-physics Simulation Code from LLNL.

Steven H. Langer, Ian Karlin, Michael M. Marinak

Proceedings of the High Performance Computing for Computational Science - VECPAR 2014 - 11th International Conference, Eugene, OR, USA, June 30, 2014

Characterizing the Impact of Program Optimizations on Power and Energy for Explicit Hydrodynamics.

Edgar A. León, Ian Karlin

Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014

2013

Exploring Traditional and Emerging Parallel Programming Models Using a Proxy Application.

Ian Karlin, Abhinav Bhatele, Jeff Keasler, Bradford L. Chamberlain, Jonathan D. Cohen, Zachary DeVito, Riyaz Haque, Dan Laney, Edward Luke, Felix Wang, David F. Richards, Martin Schulz, Charles H. Still

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

2012

Modeling the memory and performance impacts of loop fusion.

Ian Karlin, Elizabeth R. Jessup, Erik Silkensen

J. Comput. Sci., 2012

Poster: Memory and Parallelism Exploration Using the LULESH Proxy Application.

Ian Karlin, Jim McGraw, Esthela Gallardo, Jeff Keasler, Edgar A. León, Bert Still

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

Abstract: Memory and Parallelism Exploration Using the LULESH Proxy Application.

Ian Karlin, Jim McGraw, Esthela Gallardo, Jeff Keasler, Edgar A. León, Bert Still

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

2011

Parallel memory prediction for fused linear algebra kernels.

Ian Karlin, Elizabeth R. Jessup, Geoffrey Belter, Jeremy G. Siek

SIGMETRICS Perform. Evaluation Rev., 2011

2010

Understanding memory effects in the automated generation of optimized matrix algebra kernels.

Elizabeth R. Jessup, Ian Karlin, Erik Silkensen, Geoffrey Belter, Jeremy G. Siek

Proceedings of the International Conference on Computational Science, 2010

2009

Automating the generation of composed linear algebra kernels.

Geoffrey Belter, Elizabeth R. Jessup, Ian Karlin, Jeremy G. Siek

Proceedings of the ACM/IEEE Conference on High Performance Computing, 2009

2008

Build to order linear algebra kernels.

Jeremy G. Siek, Ian Karlin, Elizabeth R. Jessup

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