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ORCIDNathan R. Tallent
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2020 – today
- 2024
[c43]Aishwarya Sarkar, Sayan Ghosh, Nathan R. Tallent, Ali Jannesari:
MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs. CLUSTER 2024: 62-73- [c42]Meng Tang, Jaime Cernuda, Jie Ye, Luanzheng Guo, Nathan R. Tallent, Anthony Kougkas, Xian-He Sun:
DaYu: Optimizing Distributed Scientific Workflows by Decoding Dataflow Semantics and Dynamics. CLUSTER 2024: 357-369 - [c41]Md Nahid Newaz, Sayan Ghosh, Joshua Suetterlein, Nathan R. Tallent, Md Atiqul Mollah, Ming Hua:
Graph Analytics on Jellyfish topology. IPDPS 2024: 839-851 - [c40]Joshua Suetterlein, Stephen J. Young, J. esun Firoz, Joseph B. Manzano, Ryan D. Friese, Nathan R. Tallent, Kevin J. Barker, Timothy Stavenger:
Automatic Extraction of Network Configurations for Realistic Simulation and Validation. ISPASS 2024: 310-312 - [i8]Waqwoya Abebe, Jan Strube
, Luanzheng Guo, Nathan R. Tallent, Oceane Bel, Steven R. Spurgeon, Christina Doty, Ali Jannesari:
SAM-I-Am: Semantic Boosting for Zero-shot Atomic-Scale Electron Micrograph Segmentation. CoRR abs/2404.06638 (2024) - [i7]Chengyu Gong, Gefei Shen, Luanzheng Guo, Nathan R. Tallent, Dongfang Zhao:
OPDR: Order-Preserving Dimension Reduction for Semantic Embedding of Multimodal Scientific Data. CoRR abs/2408.10264 (2024) - [i6]Boyuan Zhang, Bo Fang, Fanjiang Ye, Yida Gu, Nathan R. Tallent, Guangming Tan, Dingwen Tao:
Overcoming Memory Constraints in Quantum Circuit Simulation with a High-Fidelity Compression Framework. CoRR abs/2410.14088 (2024) - [i5]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:
Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows. CoRR abs/2410.14943 (2024) - [i4]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:
Final Report for CHESS: Cloud, High-Performance Computing, and Edge for Science and Security. CoRR abs/2410.16093 (2024) - [i3]Aishwarya Sarkar, Sayan Ghosh, Nathan R. Tallent, Ali Jannesari:
MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs. CoRR abs/2410.22697 (2024) - 2023
- [j9]Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen, Nathan R. Tallent, Kevin J. Barker, Ang Li:
Accelerating matrix-centric graph processing on GPUs through bit-level optimizations. J. Parallel Distributed Comput. 177: 53-67 (2023) - [c39]Hyungro Lee, Luanzheng Guo, Meng Tang, Jesun Firoz, Nathan R. Tallent, Anthony Kougkas, Xian-He Sun:
Data Flow Lifecycles for Optimizing Workflow Coordination. SC 2023: 58:1-58:15 - 2022
- [j8]Sayan Ghosh, Nathan R. Tallent, Mahantesh Halappanavar:
Characterizing Performance of Graph Neighborhood Communication Patterns. IEEE Trans. Parallel Distributed Syst. 33(4): 915-928 (2022) - [c38]Ozgur O. Kilic, Nathan R. Tallent, Yasodha Suriyakumar, Chenhao Xie, Andrès Márquez, Stéphane Eranian:
MemGaze: Rapid and Effective Load-Level Memory Trace Analysis. CLUSTER 2022: 484-495 - [c37]Nathan R. Tallent:
ReWorDs 2022 Keynote: Towards Orchestrating Distributed & Data-Intensive Workflows. e-Science 2022: 442 - [c36]Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen, Nathan R. Tallent, Kevin J. Barker, Ang Li:
Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU. IPDPS 2022: 515-525 - [c35]Arun V. Sathanur, Nathan R. Tallent, Patrick Konsor, Ken Koyanagi, Ryan McLaughlin, Joseph Olivas, Michael Chynoweth:
QuaL2 M: Learning Quantitative Performance of Latency-Sensitive Code. IPDPS Workshops 2022: 913-923 - [i2]Jou-An Chen, Hsin-Hsuan Sung, Nathan R. Tallent, Kevin J. Barker, Xipeng Shen, Ang Li:
Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU. CoRR abs/2201.08560 (2022) - 2021
- [j7]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:
EXAGRAPH: Graph and combinatorial methods for enabling exascale applications. Int. J. High Perform. Comput. Appl. 35(6): 553-571 (2021) - [c34]Oceane Bel, Sinjoni Mukhopadhyay, Nathan R. Tallent, Faisal Nawab, Darrell D. E. Long:
WinnowML: Stable feature selection for maximizing prediction accuracy of time-based system modeling. IEEE BigData 2021: 3031-3041 - [c33]Oceane Bel, Joosep Pata, Jean-Roch Vlimant, Nathan R. Tallent, Justas Balcas, Maria Spiropulu:
Diolkos: improving ethernet throughput through dynamic port selection. CF 2021: 83-92 - [c32]Sayan Ghosh, Nathan R. Tallent, Marco Minutoli, Mahantesh Halappanavar, Ramesh Peri, Ananth Kalyanaraman:
Single-node partitioned-memory for huge graph analytics: cost and performance trade-offs. SC 2021: 55 - 2020
- [j6]Nitin A. Gawande, Jeff A. Daily, Charles Siegel, Nathan R. Tallent, Abhinav Vishnu:
Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing. Future Gener. Comput. Syst. 108: 1162-1172 (2020) - [j5]Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan R. Tallent, Kevin J. Barker:
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. IEEE Trans. Parallel Distributed Syst. 31(1): 94-110 (2020) - [c31]Ryan D. Friese, Burcu Ozcelik Mutlu, Nathan R. Tallent, Joshua Suetterlein, Jan Strube:
Effectively Using Remote I/O For Work Composition in Distributed Workflows. IEEE BigData 2020: 426-433 - [c30]Reet Barik, Marco Minutoli, Mahantesh Halappanavar, Nathan R. Tallent, Ananth Kalyanaraman:
Vertex Reordering for Real-World Graphs and Applications: An Empirical Evaluation. IISWC 2020: 240-251 - [c29]Oceane Bel, Kenneth Chang, Nathan R. Tallent, Dirk Düllmann, Ethan L. Miller, Faisal Nawab, Darrell D. E. Long:
Geomancy: Automated Performance Enhancement through Data Layout Optimization. ISPASS 2020: 119-120 - [c28]Ozgur O. Kilic, Nathan R. Tallent, Ryan D. Friese:
Rapid Memory Footprint Access Diagnostics. ISPASS 2020: 273-284
2010 – 2019
- 2019
- [c27]Joshua Suetterlein, Ryan D. Friese, Nathan R. Tallent, Malachi Schram:
TAZeR: Hiding the Cost of Remote I/O in Distributed Scientific Workflows. IEEE BigData 2019: 383-394 - [c26]Ozgur O. Kilic, Nathan R. Tallent, Ryan D. Friese:
Rapidly Measuring Loop Footprints. CLUSTER 2019: 1-9 - [i1]Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan R. Tallent, Kevin J. Barker:
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. CoRR abs/1903.04611 (2019) - 2018
- [c25]Alok Singh, Ilkay Altintas, Malachi Schram, Nathan R. Tallent:
Deep Learning for Enhancing Fault Tolerant Capabilities of Scientific Workflows. IEEE BigData 2018: 3905-3914 - [c24]Ryan D. Friese, Nathan R. Tallent, Malachi Schram, Mahantesh Halappanavar, Kevin J. Barker:
Optimizing Distributed Data-Intensive Workflows. CLUSTER 2018: 279-289 - [c23]Ang Li, Shuaiwen Leon Song, Jieyang Chen, Xu Liu, Nathan R. Tallent, Kevin J. Barker:
Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite. IISWC 2018: 191-202 - [c22]Tanveer Hossain Bhuiyan, Mahantesh Halappanavar, Ryan D. Friese, Hugh R. Medal, Luis de la Torre, Arun V. Sathanur, Nathan R. Tallent:
Stochastic Programming Approach for Resource Selection Under Demand Uncertainty. JSSPP 2018: 107-126 - 2017
- [c21]Ryan D. Friese, Nathan R. Tallent, Abhinav Vishnu, Darren J. Kerbyson, Adolfy Hoisie:
Generating Performance Models for Irregular Applications. IPDPS 2017: 317-326 - [c20]Nitin A. Gawande, Joshua B. Landwehr, Jeff A. Daily, Nathan R. Tallent, Abhinav Vishnu, Darren J. Kerbyson:
Scaling Deep Learning Workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing. IPDPS Workshops 2017: 399-408 - [c19]Nathan R. Tallent, Nitin A. Gawande, Charles Siegel, Abhinav Vishnu, Adolfy Hoisie:
Evaluating On-Node GPU Interconnects for Deep Learning Workloads. PMBS@SC 2017: 3-21 - [c18]Nathan R. Tallent, Darren J. Kerbyson, Adolfy Hoisie:
Representative paths analysis. SC 2017: 34 - 2016
- [c17]Nathan R. Tallent, Joseph B. Manzano, Nitin A. Gawande, Seunghwa Kang, Darren J. Kerbyson, Adolfy Hoisie, Joseph K. Cross:
Algorithm and Architecture Independent Benchmarking with SEAK. IPDPS 2016: 63-72 - [c16]Abhinav Vishnu, Hubertus Van Dam, Nathan R. Tallent, Darren J. Kerbyson, Adolfy Hoisie:
Fault Modeling of Extreme Scale Applications Using Machine Learning. IPDPS 2016: 222-231 - [c15]Nathan R. Tallent, Kevin J. Barker, Daniel G. Chavarría-Miranda, Antonino Tumeo, Mahantesh Halappanavar, Andrès Márquez, Darren J. Kerbyson, Adolfy Hoisie:
Modeling the Impact of Silicon Photonics on Graph Analytics. NAS 2016: 1-11 - [c14]Nathan R. Tallent, Kevin J. Barker, Roberto Gioiosa, Andrès Márquez, Gokcen Kestor, Leon Song, Antonino Tumeo, Darren J. Kerbyson, Adolfy Hoisie:
Assessing Advanced Technology in CENATE. NAS 2016: 1-2 - 2015
- [c13]Nitin A. Gawande, Joseph B. Manzano, Antonino Tumeo, Nathan R. Tallent, Darren J. Kerbyson, Adolfy Hoisie:
Power and performance trade-offs for Space Time Adaptive Processing. ASAP 2015: 41-48 - [c12]Nathan R. Tallent, Abhinav Vishnu, Hubertus Van Dam, Jeff Daily, Darren J. Kerbyson, Adolfy Hoisie:
Diagnosing the causes and severity of one-sided message contention. PPoPP 2015: 130-139 - [c11]Mahantesh Halappanavar, Malachi Schram, Luis de la Torre, Kevin J. Barker, Nathan R. Tallent, Darren J. Kerbyson:
Towards efficient scheduling of data intensive high energy physics workflows. WORKS@SC 2015: 3:1-3:9 - [c10]Akshay Venkatesh, Abhinav Vishnu, Khaled Hamidouche, Nathan R. Tallent, Dhabaleswar K. Panda, Darren J. Kerbyson, Adolfy Hoisie:
A case for application-oblivious energy-efficient MPI runtime. SC 2015: 29:1-29:12 - 2014
- [c9]Nathan R. Tallent, Adolfy Hoisie:
Palm: easing the burden of analytical performance modeling. ICS 2014: 221-230 - 2011
- [c8]Nathan R. Tallent, John M. Mellor-Crummey, Michael Franco, Reed Landrum, Laksono Adhianto:
Scalable fine-grained call path tracing. ICS 2011: 63-74 - [c7]Nathan R. Tallent, John M. Mellor-Crummey:
Using Sampling to Understand Parallel Program Performance. Parallel Tools Workshop 2011: 13-25 - 2010
- [j4]Laksono Adhianto, S. Banerjee, Michael W. Fagan, Mark Krentel, Gabriel Marin, John M. Mellor-Crummey, Nathan R. Tallent:
HPCTOOLKIT: tools for performance analysis of optimized parallel programs. Concurr. Comput. Pract. Exp. 22(6): 685-701 (2010) - [c6]Laksono Adhianto, John M. Mellor-Crummey, Nathan R. Tallent:
Effectively Presenting Call Path Profiles of Application Performance. ICPP Workshops 2010: 179-188 - [c5]Nathan R. Tallent, John M. Mellor-Crummey, Allan Porterfield:
Analyzing lock contention in multithreaded applications. PPoPP 2010: 269-280 - [c4]Nathan R. Tallent, Laksono Adhianto, John M. Mellor-Crummey:
Scalable Identification of Load Imbalance in Parallel Executions Using Call Path Profiles. SC 2010: 1-11
2000 – 2009
- 2009
- [j3]Nathan R. Tallent, John M. Mellor-Crummey:
Identifying Performance Bottlenecks in Work-Stealing Computations. Computer 42(11): 44-50 (2009) - [c3]Nathan R. Tallent, John M. Mellor-Crummey, Michael W. Fagan:
Binary analysis for measurement and attribution of program performance. PLDI 2009: 441-452 - [c2]Nathan R. Tallent, John M. Mellor-Crummey:
Effective performance measurement and analysis of multithreaded applications. PPoPP 2009: 229-240 - [c1]Nathan R. Tallent, John M. Mellor-Crummey, Laksono Adhianto, Michael W. Fagan, Mark Krentel:
Diagnosing performance bottlenecks in emerging petascale applications. SC 2009 - 2008
- [j2]Jean Utke, Uwe Naumann, Michael W. Fagan, Nathan R. Tallent, Michelle Mills Strout, Patrick Heimbach, Chris Hill, Carl Wunsch:
OpenAD/F: A Modular Open-Source Tool for Automatic Differentiation of Fortran Codes. ACM Trans. Math. Softw. 34(4): 18:1-18:36 (2008) - 2002
- [j1]John M. Mellor-Crummey, Robert J. Fowler, Gabriel Marin, Nathan R. Tallent:
HPCVIEW: A Tool for Top-down Analysis of Node Performance. J. Supercomput. 23(1): 81-104 (2002)
Coauthor Index
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last updated on 2024-12-03 21:21 CET by the dblp team
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