Nathan R. Tallent

According to our database, Nathan R. Tallent authored at least 59 papers between 2002 and 2024.

Collaborative distances:

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2024

Final Report for CHESS: Cloud, High-Performance Computing, and Edge for Science and Security.

Nathan R. Tallent, Jan Strube, Luanzheng Guo, Hyungro Lee, Jesun Firoz, Sayan Ghosh, Bo Fang, Oceane Bel, Steven R. Spurgeon, Sarah Akers, Christina Doty, Erol Cromwell

CoRR, 2024

Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows.

Rafael Ferreira da Silva, Deborah Bard, Kyle Chard, Shaun De Witt, Ian T. Foster, Tom Gibbs, Carole A. Goble, William F. Godoy, Johan Gustafsson, Utz-Uwe Haus, Stephen Hudson, Shantenu Jha, Laila Los, Drew Paine, Frédéric Suter, Logan T. Ward, Sean R. Wilkinson, Marcos Amaris, Yadu N. Babuji, Jonathan Bader, Riccardo Balin, Daniel Balouek, Sarah J. Beecroft, Khalid Belhajjame, Rajat Bhattarai, Wes Brewer, Paul Brunk, Silvina Caíno-Lores, Henri Casanova, Daniela Cassol, Jared Coleman, Tainã Coleman, Iacopo Colonnelli, Anderson Andrei Da Silva, Daniel de Oliveira, Pascal Elahi, Nour Elfaramawy, Wael R. Elwasif, Brian Etz, Thomas Fahringer, Wesley Ferreira, Rosa Filgueira, Jacob Fosso Tande, Luiz Gadelha, Andy Gallo, Daniel Garijo, Yiannis Georgiou, Philipp Gritsch, Patricia Grubel, Amal Gueroudji, Quentin Guilloteau, Carlo Hamalainen, Rolando P. Hong Enriquez, Lauren Huet, Kevin Hunter Kesling, Paula Iborra, Shiva Jahangiri, Jan Janssen, Joe Jordan, Sehrish Kanwal, Liliane N. O. Kunstmann, Fabian Lehmann, Ulf Leser, Chen Li, Peini Liu, Jakob Lüttgau, Richard Lupat, José M. Fernández, Ketan Maheshwari, Tanu Malik, Jack Marquez, Motohiko Matsuda, Doriana Medic, Somayeh Mohammadi, Alberto Mulone, John-Luke Navarro, Kin Wai Ng, Klaus Nölp, Bruno de Paula Kinoshita, Ryan Prout, Michael R. Crusoe, Sashko Ristov, Stefan A Robila, Daniel Rosendo, Billy Rowell, Jedrzej Rybicki, Hector Sanchez, Nishant Saurabh, Sumit Kumar Saurav, Tom Scogland, Dinindu Senanayake, Woong Shin, Raül Sirvent, Tyler J. Skluzacek, Barry Sly-Delgado, Stian Soiland-Reyes, Abel Souza, Renan Souza, Domenico Talia, Nathan R. Tallent

CoRR, 2024

Overcoming Memory Constraints in Quantum Circuit Simulation with a High-Fidelity Compression Framework.

Boyuan Zhang, Bo Fang, Fanjiang Ye, Yida Gu, Nathan R. Tallent, Guangming Tan, Dingwen Tao

CoRR, 2024

OPDR: Order-Preserving Dimension Reduction for Semantic Embedding of Multimodal Scientific Data.

Chengyu Gong, Gefei Shen, Luanzheng Guo, Nathan R. Tallent, Dongfang Zhao

CoRR, 2024

SAM-I-Am: Semantic Boosting for Zero-shot Atomic-Scale Electron Micrograph Segmentation.

Waqwoya Abebe, Jan Strube, Luanzheng Guo, Nathan R. Tallent, Oceane Bel, Steven R. Spurgeon, Christina Doty, Ali Jannesari

CoRR, 2024

MemFriend: Understanding Memory Performance with Spatial-Temporal Affinity.

Yasodha Suriyakumar, Nathan R. Tallent, Andres Marquez, Karen L. Karavanic, Ozgur O. Kilic

Proceedings of the International Symposium on Memory Systems, 2024

Automatic Extraction of Network Configurations for Realistic Simulation and Validation.

Joshua Suetterlein, Stephen J. Young, J. esun Firoz, Joseph B. Manzano, Ryan D. Friese, Nathan R. Tallent, Kevin J. Barker, Timothy Stavenger

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2024

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing.

Shiyue Hou, Nathan R. Tallent, Li Wang, Ningfang Mi

Proceedings of the International Symposium on Networks, Computers and Communications, 2024

Graph Analytics on Jellyfish topology.

Md Nahid Newaz, Sayan Ghosh, Joshua Suetterlein, Nathan R. Tallent, Md Atiqul Mollah, Ming Hua

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

DaYu: Optimizing Distributed Scientific Workflows by Decoding Dataflow Semantics and Dynamics.

Meng Tang, Jaime Cernuda, Jie Ye, Luanzheng Guo, Nathan R. Tallent, Anthony Kougkas, Xian-He Sun

Proceedings of the IEEE International Conference on Cluster Computing, 2024

MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs.

Aishwarya Sarkar, Sayan Ghosh, Nathan R. Tallent, Ali Jannesari

Proceedings of the IEEE International Conference on Cluster Computing, 2024

2023

Accelerating matrix-centric graph processing on GPUs through bit-level optimizations.

Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen, Nathan R. Tallent, Kevin J. Barker, Ang Li

J. Parallel Distributed Comput., July, 2023

Data Flow Lifecycles for Optimizing Workflow Coordination.

Hyungro Lee, Luanzheng Guo, Meng Tang, Jesun Firoz, Nathan R. Tallent, Anthony Kougkas, Xian-He Sun

Proceedings of the International Conference for High Performance Computing, 2023

2022

Characterizing Performance of Graph Neighborhood Communication Patterns.

Sayan Ghosh, Nathan R. Tallent, Mahantesh Halappanavar

IEEE Trans. Parallel Distributed Syst., 2022

QuaL² M: Learning Quantitative Performance of Latency-Sensitive Code.

Arun V. Sathanur, Nathan R. Tallent, Patrick Konsor, Ken Koyanagi, Ryan McLaughlin, Joseph Olivas, Michael Chynoweth

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

Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU.

Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen, Nathan R. Tallent, Kevin J. Barker, Ang Li

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

ReWorDs 2022 Keynote: Towards Orchestrating Distributed & Data-Intensive Workflows.

Nathan R. Tallent

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

MemGaze: Rapid and Effective Load-Level Memory Trace Analysis.

Ozgur O. Kilic, Nathan R. Tallent, Yasodha Suriyakumar, Chenhao Xie, Andrès Márquez, Stéphane Eranian

Proceedings of the IEEE International Conference on Cluster Computing, 2022

2021

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications.

Seher Acer, Ariful Azad, Erik G. Boman, Aydin Buluç, Karen D. Devine, S. M. Ferdous, Nitin Gawande, Sayan Ghosh, Mahantesh Halappanavar, Ananth Kalyanaraman, Arif Khan, Marco Minutoli, Alex Pothen, Sivasankaran Rajamanickam, Oguz Selvitopi, Nathan R. Tallent, Antonino Tumeo

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

Single-node partitioned-memory for huge graph analytics: cost and performance trade-offs.

Sayan Ghosh, Nathan R. Tallent, Marco Minutoli, Mahantesh Halappanavar, Ramesh Peri, Ananth Kalyanaraman

Proceedings of the International Conference for High Performance Computing, 2021

Diolkos: improving ethernet throughput through dynamic port selection.

Oceane Bel, Joosep Pata, Jean-Roch Vlimant, Nathan R. Tallent, Justas Balcas, Maria Spiropulu

Proceedings of the CF '21: Computing Frontiers Conference, 2021

WinnowML: Stable feature selection for maximizing prediction accuracy of time-based system modeling.

Oceane Bel, Sinjoni Mukhopadhyay, Nathan R. Tallent, Faisal Nawab, Darrell D. E. Long

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect.

Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan R. Tallent, Kevin J. Barker

IEEE Trans. Parallel Distributed Syst., 2020

Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing.

Nitin A. Gawande, Jeff A. Daily, Charles Siegel, Nathan R. Tallent, Abhinav Vishnu

Future Gener. Comput. Syst., 2020

Rapid Memory Footprint Access Diagnostics.

Ozgur O. Kilic, Nathan R. Tallent, Ryan D. Friese

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2020

Geomancy: Automated Performance Enhancement through Data Layout Optimization.

Oceane Bel, Kenneth Chang, Nathan R. Tallent, Dirk Düllmann, Ethan L. Miller, Faisal Nawab, Darrell D. E. Long

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2020

Vertex Reordering for Real-World Graphs and Applications: An Empirical Evaluation.

Reet Barik, Marco Minutoli, Mahantesh Halappanavar, Nathan R. Tallent, Ananth Kalyanaraman

Proceedings of the IEEE International Symposium on Workload Characterization, 2020

Effectively Using Remote I/O For Work Composition in Distributed Workflows.

Ryan D. Friese, Burcu Ozcelik Mutlu, Nathan R. Tallent, Joshua Suetterlein, Jan Strube

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Rapidly Measuring Loop Footprints.

Ozgur O. Kilic, Nathan R. Tallent, Ryan D. Friese

Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

TAZeR: Hiding the Cost of Remote I/O in Distributed Scientific Workflows.

Joshua Suetterlein, Ryan D. Friese, Nathan R. Tallent, Malachi Schram

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Stochastic Programming Approach for Resource Selection Under Demand Uncertainty.

Tanveer Hossain Bhuiyan, Mahantesh Halappanavar, Ryan D. Friese, Hugh R. Medal, Luis de la Torre, Arun V. Sathanur, Nathan R. Tallent

Proceedings of the Job Scheduling Strategies for Parallel Processing, 2018

Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite.

Ang Li, Shuaiwen Leon Song, Jieyang Chen, Xu Liu, Nathan R. Tallent, Kevin J. Barker

Proceedings of the 2018 IEEE International Symposium on Workload Characterization, 2018

Optimizing Distributed Data-Intensive Workflows.

Ryan D. Friese, Nathan R. Tallent, Malachi Schram, Mahantesh Halappanavar, Kevin J. Barker

Proceedings of the IEEE International Conference on Cluster Computing, 2018

Deep Learning for Enhancing Fault Tolerant Capabilities of Scientific Workflows.

Alok Singh, Ilkay Altintas, Malachi Schram, Nathan R. Tallent

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Representative paths analysis.

Nathan R. Tallent, Darren J. Kerbyson, Adolfy Hoisie

Proceedings of the International Conference for High Performance Computing, 2017

Evaluating On-Node GPU Interconnects for Deep Learning Workloads.

Nathan R. Tallent, Nitin A. Gawande, Charles Siegel, Abhinav Vishnu, Adolfy Hoisie

Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, 2017

Scaling Deep Learning Workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing.

Nitin A. Gawande, Joshua B. Landwehr, Jeff A. Daily, Nathan R. Tallent, Abhinav Vishnu, Darren J. Kerbyson

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

Generating Performance Models for Irregular Applications.

Ryan D. Friese, Nathan R. Tallent, Abhinav Vishnu, Darren J. Kerbyson, Adolfy Hoisie

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

2016

Assessing Advanced Technology in CENATE.

Nathan R. Tallent, Kevin J. Barker, Roberto Gioiosa, Andrès Márquez, Gokcen Kestor, Leon Song, Antonino Tumeo, Darren J. Kerbyson, Adolfy Hoisie

Proceedings of the IEEE International Conference on Networking, 2016

Modeling the Impact of Silicon Photonics on Graph Analytics.

Nathan R. Tallent, Kevin J. Barker, Daniel G. Chavarría-Miranda, Antonino Tumeo, Mahantesh Halappanavar, Andrès Márquez, Darren J. Kerbyson, Adolfy Hoisie

Proceedings of the IEEE International Conference on Networking, 2016

Fault Modeling of Extreme Scale Applications Using Machine Learning.

Abhinav Vishnu, Hubertus Van Dam, Nathan R. Tallent, Darren J. Kerbyson, Adolfy Hoisie

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

Algorithm and Architecture Independent Benchmarking with SEAK.

Nathan R. Tallent, Joseph B. Manzano, Nitin A. Gawande, Seunghwa Kang, Darren J. Kerbyson, Adolfy Hoisie, Joseph K. Cross

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

2015

A case for application-oblivious energy-efficient MPI runtime.

Akshay Venkatesh, Abhinav Vishnu, Khaled Hamidouche, Nathan R. Tallent, Dhabaleswar K. Panda, Darren J. Kerbyson, Adolfy Hoisie

Proceedings of the International Conference for High Performance Computing, 2015

Towards efficient scheduling of data intensive high energy physics workflows.

Mahantesh Halappanavar, Malachi Schram, Luis de la Torre, Kevin J. Barker, Nathan R. Tallent, Darren J. Kerbyson

Proceedings of the 10th Workshop on Workflows in Support of Large-Scale Science, 2015

Diagnosing the causes and severity of one-sided message contention.

Nathan R. Tallent, Abhinav Vishnu, Hubertus Van Dam, Jeff Daily, Darren J. Kerbyson, Adolfy Hoisie

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

Power and performance trade-offs for Space Time Adaptive Processing.

Nitin A. Gawande, Joseph B. Manzano, Antonino Tumeo, Nathan R. Tallent, Darren J. Kerbyson, Adolfy Hoisie

Proceedings of the 26th IEEE International Conference on Application-specific Systems, 2015

2014

Palm: easing the burden of analytical performance modeling.

Nathan R. Tallent, Adolfy Hoisie

Proceedings of the 2014 International Conference on Supercomputing, 2014

2011

Using Sampling to Understand Parallel Program Performance.

Nathan R. Tallent, John M. Mellor-Crummey

Proceedings of the Tools for High Performance Computing 2011, 2011

Scalable fine-grained call path tracing.

Nathan R. Tallent, John M. Mellor-Crummey, Michael Franco, Reed Landrum, Laksono Adhianto

Proceedings of the 25th International Conference on Supercomputing, 2011, Tucson, AZ, USA, May 31, 2011

2010

HPCTOOLKIT: tools for performance analysis of optimized parallel programs.

Laksono Adhianto, S. Banerjee, Michael W. Fagan, Mark Krentel, Gabriel Marin, John M. Mellor-Crummey, Nathan R. Tallent

Concurr. Comput. Pract. Exp., 2010

Scalable Identification of Load Imbalance in Parallel Executions Using Call Path Profiles.

Nathan R. Tallent, Laksono Adhianto, John M. Mellor-Crummey

Proceedings of the Conference on High Performance Computing Networking, 2010

Analyzing lock contention in multithreaded applications.

Nathan R. Tallent, John M. Mellor-Crummey, Allan Porterfield

Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2010

Effectively Presenting Call Path Profiles of Application Performance.

Laksono Adhianto, John M. Mellor-Crummey, Nathan R. Tallent

Proceedings of the 39th International Conference on Parallel Processing, 2010

2009

Identifying Performance Bottlenecks in Work-Stealing Computations.

Nathan R. Tallent, John M. Mellor-Crummey

Computer, 2009

Diagnosing performance bottlenecks in emerging petascale applications.

Nathan R. Tallent, John M. Mellor-Crummey, Laksono Adhianto, Michael W. Fagan, Mark Krentel

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

Effective performance measurement and analysis of multithreaded applications.

Nathan R. Tallent, John M. Mellor-Crummey

Proceedings of the 14th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009

Binary analysis for measurement and attribution of program performance.

Nathan R. Tallent, John M. Mellor-Crummey, Michael W. Fagan

Proceedings of the 2009 ACM SIGPLAN Conference on Programming Language Design and Implementation, 2009

2008

OpenAD/F: A Modular Open-Source Tool for Automatic Differentiation of Fortran Codes.

Jean Utke, Uwe Naumann, Michael W. Fagan, Nathan R. Tallent, Michelle Mills Strout, Patrick Heimbach, Chris Hill, Carl Wunsch

ACM Trans. Math. Softw., 2008

2002

HPCVIEW: A Tool for Top-down Analysis of Node Performance.

John M. Mellor-Crummey, Robert J. Fowler, Gabriel Marin, Nathan R. Tallent

J. Supercomput., 2002