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ORCIDStephan J. Eidenbenz
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- affiliation: Los Alamos National Laboratory, NM, USA
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2020 – today
- 2024
[j35]Yuri Alexeev, Maximilian Amsler, Marco Antonio Barroca, Sanzio Bassini, Torey Battelle, Daan Camps, David Casanova, Young Jay Choi, Frederic T. Chong, Charles Chung, Christopher Codella, Antonio D. Córcoles, James Cruise, Alberto Di Meglio, Ivan Duran, Thomas Eckl, Sophia E. Economou, Stephan J. Eidenbenz, Bruce Elmegreen, Clyde Fare, Ismael Faro, Cristina Sanz Fernández, Rodrigo Neumann Barros Ferreira
, Keisuke Fuji, Bryce Fuller, Laura Gagliardi, Giulia Galli, Jennifer R. Glick, Isacco Gobbi, Pranav Gokhale, Salvador de la Puente Gonzalez, Johannes Greiner, Bill Gropp, Michele Grossi, Emanuel Gull, Burns Healy, Matthew R. Hermes, Benchen Huang, Travis S. Humble, Nobuyasu Ito, Artur F. Izmaylov, Ali Javadi-Abhari, Douglas M. Jennewein, Shantenu Jha, Liang Jiang, Barbara Jones, Wibe Albert de Jong, Petar Jurcevic, William M. Kirby, Stefan Kister, Masahiro Kitagawa, Joel Klassen, Katherine Klymko, Kwangwon Koh, Masaaki Kondo, Doga Murat Kürkçüoglu, Krzysztof Kurowski, Teodoro Laino, Ryan Landfield, Matthew L. Leininger, Vicente Leyton-Ortega, Ang Li, Meifeng Lin, Junyu Liu, Nicolás Lorente, André Luckow, Simon Martiel, Francisco Martín-Fernández, Margaret Martonosi, Claire Marvinney, Arcesio Castañeda Medina, Dirk Merten, Antonio Mezzacapo, Kristel Michielsen, Abhishek Mitra, Tushar Mittal, Kyungsun Moon, Joel Moore, Sarah Mostame, Mario Motta, Young-Hye Na, Yunseong Nam, Prineha Narang, Yu-ya Ohnishi, Daniele Ottaviani, Matthew Otten, Scott Pakin, Vincent R. Pascuzzi, Edwin Pednault, Tomasz Piontek, Jed Pitera, Patrick Rall, Gokul Subramanian Ravi, Niall Robertson, Matteo A. C. Rossi, Piotr Rydlichowski, Hoon Ryu, Georgy Samsonidze, Mitsuhisa Sato, Nishant Saurabh, Vidushi Sharma, Kunal Sharma, Soyoung Shin, George Slessman, Mathias Steiner, Iskandar Sitdikov, In-Saeng Suh, Eric D. Switzer, Wei Tang, Joel Thompson, Synge Todo, Minh C. Tran, Dimitar Trenev, Christian Trott, Huan-Hsin Tseng, Norm M. Tubman, Esin Tureci, David García Valiñas, Sofia Vallecorsa, Christopher Wever, Konrad Wojciechowski, Xiaodi Wu, Shinjae Yoo, Nobuyuki Yoshioka, Victor Wen-zhe Yu, Seiji Yunoki, Sergiy Zhuk, Dmitry Zubarev:
Quantum-centric supercomputing for materials science: A perspective on challenges and future directions. Future Gener. Comput. Syst. 160: 666-710 (2024)- [j34]Samantha V. Barron, Daniel J. Egger, Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz, Matthis Lehmkuehler, Stefan Woerner:
Provable bounds for noise-free expectation values computed from noisy samples. Nat. Comput. Sci. 4(11): 865-875 (2024) - [j33]Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov:
Distributed out-of-memory NMF on CPU/GPU architectures. J. Supercomput. 80(3): 3970-3999 (2024) - [j32]Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov:
Correction to: Distributed out-of-memory NMF on CPU/GPU architectures. J. Supercomput. 80(4): 5731-5732 (2024) - [j31]Erik Skau, Andrew Hollis, Stephan J. Eidenbenz, Kim Ø. Rasmussen, Boian S. Alexandrov:
Generating Hidden Markov Models from Process Models Through Nonnegative Tensor Factorization. ACM Trans. Model. Comput. Simul. 34(4): 21:1-21:19 (2024) - [c121]Joel Rajakumar, John K. Golden, Andreas Bärtschi, Stephan J. Eidenbenz:
Trainability Barriers in Low-Depth QAOA Landscapes. CF 2024 - [c120]Christo Meriwether Keller, Stephan J. Eidenbenz, Andreas Bärtschi, Daniel O'Malley, John K. Golden, Satyajayant Misra:
Hierarchical Multigrid Ansatz for Variational Quantum Algorithms. ISC 2024: 1-11 - [i41]Joel Rajakumar, John K. Golden, Andreas Bärtschi, Stephan J. Eidenbenz:
Trainability Barriers in Low-Depth QAOA Landscapes. CoRR abs/2402.10188 (2024) - [i40]Reuben Tate, Stephan J. Eidenbenz:
Guarantees on Warm-Started QAOA: Single-Round Approximation Ratios for 3-Regular MAXCUT and Higher-Round Scaling Limits. CoRR abs/2402.12631 (2024) - [i39]Shamminuj Aktar, Andreas Bärtschi, Diane Oyen, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy:
Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation. CoRR abs/2405.08100 (2024) - [i38]Sean Feeney, Reuben Tate, Stephan J. Eidenbenz:
The Better Solution Probability Metric: Optimizing QAOA to Outperform its Warm-Start Solution. CoRR abs/2409.09012 (2024) - [i37]Jad Salem, Reuben Tate, Stephan J. Eidenbenz:
Expected Maximin Fairness in Max-Cut and other Combinatorial Optimization Problems. CoRR abs/2410.02589 (2024) - [i36]Nandakishore Santhi, Stephan J. Eidenbenz, Brian Key, George Tompkins:
Generative Discrete Event Process Simulation for Hidden Markov Models to Predict Competitor Time-to-Market. CoRR abs/2411.04266 (2024) - 2023
- [c119]Shamminuj Aktar, Abdel-Hameed A. Badawy, Andreas Bärtschi, Stephan J. Eidenbenz:
Scalable Experimental Bounds for Dicke and GHZ States Fidelities. CF 2023: 176-184 - [c118]Hamdy Abdelkhalik, Shamminuj Aktar, Yehia Arafa, Atanu Barai, Gopinath Chennupati, Nandakishore Santhi, Nishant Panda, Nirmal Prajapati, Nazmul Haque Turja, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy:
BB-ML: Basic Block Performance Prediction using Machine Learning Techniques. ICPADS 2023: 1975-1982 - [c117]Atanu Barai, Nandakishore Santhi, Abdur Razzak, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy:
LLVM Static Analysis for Program Characterization and Memory Reuse Profile Estimation. MEMSYS 2023: 3:1-3:6 - [c116]John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz:
The Quantum Alternating Operator Ansatz for Satisfiability Problems. QCE 2023: 307-312 - [c115]Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy, Diane Oyen, Stephan J. Eidenbenz:
Predicting Expressibility of Parameterized Quantum Circuits Using Graph Neural Network. QCE 2023: 401-402 - [c114]John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz:
Numerical Evidence for Exponential Speed-Up of QAOA over Unstructured Search for Approximate Constrained Optimization. QCE 2023: 496-505 - [c113]Elijah Pelofske, Andreas Bärtschi, John K. Golden, Stephan J. Eidenbenz:
High-Round QAOA for MAX $k$-SAT on Trapped Ion NISQ Devices. QCE 2023: 506-517 - [c112]John K. Golden, Andreas Bärtschi, Dan O'Malley, Elijah Pelofske, Stephan J. Eidenbenz:
JuliQAOA: Fast, Flexible QAOA Simulation. SC Workshops 2023: 1454-1459 - [c111]Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz:
Quantum Annealing vs. QAOA: 127 Qubit Higher-Order Ising Problems on NISQ Computers. ISC 2023: 240-258 - [i35]Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz:
Quantum Annealing vs. QAOA: 127 Qubit Higher-Order Ising Problems on NISQ Computers. CoRR abs/2301.00520 (2023) - [i34]John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz:
The Quantum Alternating Operator Ansatz for Satisfiability Problems. CoRR abs/2301.11292 (2023) - [i33]Elijah Pelofske, Andreas Bärtschi, John K. Golden, Stephan J. Eidenbenz:
High-Round QAOA for MAX k-SAT on Trapped Ion NISQ Devices. CoRR abs/2306.03238 (2023) - [i32]Elijah Pelofske, Vincent Russo, Ryan LaRose, Andrea Mari, Dan Strano, Andreas Bärtschi, Stephan J. Eidenbenz, William J. Zeng:
Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation. CoRR abs/2306.15863 (2023) - [i31]Naphan Benchasattabuse, Andreas Bärtschi, Luis Pedro García-Pintos, John K. Golden, Nathan Lemons, Stephan J. Eidenbenz:
Lower Bounds on Number of QAOA Rounds Required for Guaranteed Approximation Ratios. CoRR abs/2308.15442 (2023) - [i30]Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz, Bryan Garcia, Boris Kiefer:
Probing Quantum Telecloning on Superconducting Quantum Processors. CoRR abs/2308.15579 (2023) - [i29]Atanu Barai, Nandakishore Santhi, Abdur Razzak, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy:
LLVM Static Analysis for Program Characterization and Memory Reuse Profile Estimation. CoRR abs/2311.12883 (2023) - [i28]Samantha V. Barron, Daniel J. Egger, Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz, Matthis Lehmkuehler, Stefan Woerner:
Provable bounds for noise-free expectation values computed from noisy samples. CoRR abs/2312.00733 (2023) - [i27]Elijah Pelofske, Andreas Bärtschi, Lukasz Cincio, John K. Golden, Stephan J. Eidenbenz:
Scaling Whole-Chip QAOA for Higher-Order Ising Spin Glass Models on Heavy-Hex Graphs. CoRR abs/2312.00997 (2023) - [i26]Christo Meriwether Keller, Stephan J. Eidenbenz, Andreas Bärtschi, Daniel O'Malley, John K. Golden, Satyajayant Misra:
Hierarchical Multigrid Ansatz for Variational Quantum Algorithms. CoRR abs/2312.15048 (2023) - 2022
- [j30]Atanu Barai, Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
PPT-Multicore: performance prediction of OpenMP applications using reuse profiles and analytical modeling. J. Supercomput. 78(2): 2354-2385 (2022) - [c110]Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz:
Optimized Telecloning Circuits: Theory and Practice of Nine NISQ Clones. ICRC 2022: 51-56 - [c109]Andreas Bärtschi, Stephan J. Eidenbenz:
Short-Depth Circuits for Dicke State Preparation. QCE 2022: 87-96 - [c108]Elijah Pelofske, Andreas Bärtschi, Bryan Garcia, Boris Kiefer, Stephan J. Eidenbenz:
Quantum Telecloning on NISQ Computers. QCE 2022: 605-616 - [d1]Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz:
Quantum Volume in Practice: What Users Can Expect from NISQ Devices Dataset. IEEE DataPort, 2022
- [i25]John K. Golden, Andreas Bärtschi, Stephan J. Eidenbenz, Daniel O'Malley:
Evidence for Super-Polynomial Advantage of QAOA over Unstructured Search. CoRR abs/2202.00648 (2022) - [i24]Shamminuj Aktar, Hamdy Abdelkhalik, Nazmul Haque Turja, Yehia Arafa, Atanu Barai, Nishant Panda, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy:
BB-ML: Basic Block Performance Prediction using Machine Learning Techniques. CoRR abs/2202.07798 (2022) - [i23]Ismael Boureima, Manish Bhattarai, Maksim Ekin Eren, Erik Skau, Philip Romero, Stephan J. Eidenbenz, Boian S. Alexandrov:
Distributed Out-of-Memory NMF of Dense and Sparse Data on CPU/GPU Architectures with Automatic Model Selection for Exascale Data. CoRR abs/2202.09518 (2022) - [i22]Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz:
Quantum Volume in Practice: What Users Can Expect from NISQ Devices. CoRR abs/2203.03816 (2022) - [i21]Elijah Pelofske, Andreas Bärtschi, Bryan Garcia, Boris Kiefer, Stephan J. Eidenbenz:
Quantum Telecloning on NISQ Computers. CoRR abs/2205.00125 (2022) - [i20]Andreas Bärtschi, Stephan J. Eidenbenz:
Short-Depth Circuits for Dicke State Preparation. CoRR abs/2207.09998 (2022) - [i19]Erik Skau, Andrew Hollis, Stephan J. Eidenbenz, Kim Ø. Rasmussen, Boian S. Alexandrov:
Process Modeling, Hidden Markov Models, and Non-negative Tensor Factorization with Model Selection. CoRR abs/2210.01060 (2022) - [i18]Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy, Stephan J. Eidenbenz:
Scalable Experimental Bounds for Entangled Quantum State Fidelities. CoRR abs/2210.03048 (2022) - [i17]Elijah Pelofske, Andreas Bärtschi, Stephan J. Eidenbenz:
Optimized Telecloning Circuits: Theory and Practice of Nine NISQ Clones. CoRR abs/2210.10164 (2022) - 2021
- [j29]Gopinath Chennupati, Nandakishore Santhi, Phillip Romero, Stephan J. Eidenbenz:
Machine Learning-enabled Scalable Performance Prediction of Scientific Codes. ACM Trans. Model. Comput. Simul. 31(2): 11:1-11:28 (2021) - [c107]Ali Eker, Yehia Arafa, Abdel-Hameed A. Badawy, Nandakishore Santhi, Stephan J. Eidenbenz, Dmitry Ponomarev:
Load-Aware Dynamic Time Synchronization in Parallel Discrete Event Simulation. SIGSIM-PADS 2021: 95-105 - [c106]John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz:
Threshold-Based Quantum Optimization. QCE 2021: 137-147 - [c105]Elijah Pelofske, John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz:
Sampling on NISQ Devices: "Who's the Fairest One of All?". QCE 2021: 207-217 - [c104]Yehia Arafa, Abdel-Hameed A. Badawy, Ammar ElWazir, Atanu Barai, Ali Eker, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
Hybrid, scalable, trace-driven performance modeling of GPGPUs. SC 2021: 53 - [i16]John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz:
QAOA-based Fair Sampling on NISQ Devices. CoRR abs/2101.03258 (2021) - [i15]Atanu Barai, Gopinath Chennupati, Nandakishore Santhi, Abdel-Hameed A. Badawy, Yehia Arafa, Stephan J. Eidenbenz:
PPT-SASMM: Scalable Analytical Shared Memory Model: Predicting the Performance of Multicore Caches from a Single-Threaded Execution Trace. CoRR abs/2103.10635 (2021) - [i14]Atanu Barai, Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
PPT-Multicore: Performance Prediction of OpenMP applications using Reuse Profiles and Analytical Modeling. CoRR abs/2104.05102 (2021) - [i13]John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz:
Threshold-Based Quantum Optimization. CoRR abs/2106.13860 (2021) - [i12]Elijah Pelofske, John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz:
Sampling on NISQ Devices: "Who's the Fairest One of All?". CoRR abs/2107.06468 (2021) - [i11]Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy, Stephan J. Eidenbenz:
A Divide-and-Conquer Approach to Dicke State Preparation. CoRR abs/2112.12435 (2021) - 2020
- [j28]Poornima Haridas, Gopinath Chennupati, Nandakishore Santhi, Phillip Romero, Stephan J. Eidenbenz:
Code Characterization With Graph Convolutions and Capsule Networks. IEEE Access 8: 136307-136315 (2020) - [c103]Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz, Nandakishore Santhi:
Verified instruction-level energy consumption measurement for NVIDIA GPUs. CF 2020: 60-70 - [c102]Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Atanu Barai, Nandakishore Santhi, Stephan J. Eidenbenz:
Fast, accurate, and scalable memory modeling of GPGPUs using reuse profiles. ICS 2020: 31:1-31:12 - [c101]Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz, Nandakishore Santhi:
NVIDIA GPGPUs Instructions Energy Consumption. ISPASS 2020: 110-112 - [c100]Atanu Barai, Gopinath Chennupati, Nandakishore Santhi, Abdel-Hameed A. Badawy, Yehia Arafa, Stephan J. Eidenbenz:
PPT-SASMM: Scalable Analytical Shared Memory Model: Predicting the Performance of Multicore Caches from a Single-Threaded Execution Trace. MEMSYS 2020: 341-351 - [c99]Andreas Bärtschi, Stephan J. Eidenbenz:
Grover Mixers for QAOA: Shifting Complexity from Mixer Design to State Preparation. QCE 2020: 72-82 - [c98]Jeremy Cook, Stephan J. Eidenbenz, Andreas Bärtschi:
The Quantum Alternating Operator Ansatz on Maximum k-Vertex Cover. QCE 2020: 83-92 - [c97]Stefanie Zbinden, Andreas Bärtschi, Hristo N. Djidjev, Stephan J. Eidenbenz:
Embedding Algorithms for Quantum Annealers with Chimera and Pegasus Connection Topologies. ISC 2020: 187-206 - [i10]Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz, Nandakishore Santhi:
Verified Instruction-Level Energy Consumption Measurement for NVIDIA GPUs. CoRR abs/2002.07795 (2020) - [i9]Andreas Bärtschi, Stephan J. Eidenbenz:
Grover Mixers for QAOA: Shifting Complexity from Mixer Design to State Preparation. CoRR abs/2006.00354 (2020) - [i8]Gopinath Chennupati, Nandakishore Santhi, Phillip Romero, Stephan J. Eidenbenz:
Machine Learning Enabled Scalable Performance Prediction of Scientific Codes. CoRR abs/2010.04212 (2020)
2010 – 2019
- 2019
- [j27]Joan Boyar, Stephan J. Eidenbenz, Lene M. Favrholdt, Michal Kotrbcík, Kim S. Larsen:
Online Dominating Set. Algorithmica 81(5): 1938-1964 (2019) - [j26]Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
PPT-GPU: Scalable GPU Performance Modeling. IEEE Comput. Archit. Lett. 18: 55-58 (2019) - [c96]Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
POSTER: GPUs Pipeline Latency Analysis. ASAP 2019: 139 - [c95]Andreas Bärtschi, Stephan J. Eidenbenz:
Deterministic Preparation of Dicke States. FCT 2019: 126-139 - [c94]Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
Low Overhead Instruction Latency Characterization for NVIDIA GPGPUs. HPEC 2019: 1-8 - [c93]Yehia Arafa, Gopinath Chennupati, Atanu Barai, Abdel-Hameed A. Badawy, Nandakishore Santhi, Stephan J. Eidenbenz:
GPUs Cache Performance Estimation using Reuse Distance Analysis. IPCCC 2019: 1-8 - [c92]Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
Scalable Performance Prediction of Codes with Memory Hierarchy and Pipelines. SIGSIM-PADS 2019: 13-24 - [i7]Carleton Coffrin, James Arnold, Stephan J. Eidenbenz, Derek Aberle, John Ambrosiano, Zachary K. Baker, Sara Brambilla, Michael J. Brown, K. Nolan Carter, Pinghan Chu, Patrick Conry, Keeley Costigan, Ariane Eberhardt, David M. Fobes, Adam Gausmann, Sean N. Harris, Donovan Heimer, Marlin Holmes, Bill Junor, Csaba Kiss, Steve Linger, Rodman R. Linn, Li-Ta Lo, Jonathan MacCarthy, Omar Marcillo, Clay McGinnis, Alexander McQuarters, Eric Michalak, Arvind Mohan, Matt Nelson, Diane Oyen, Nidhi Parikh, Donatella Pasqualini, Aaron S. Pope, Reid B. Porter, Chris Rawlings, Hannah Reinbolt, Reid D. Rivenburgh, Philip Romero, Kevin Schoonover, Alexei N. Skurikhin, Daniel R. Tauritz, Dima Tretiak, Zhehui Wang, James Wernicke, Brad Wolfe, Phillip Wolfram, Jonathan Woodring:
The ISTI Rapid Response on Exploring Cloud Computing 2018. CoRR abs/1901.01331 (2019) - [i6]Andreas Bärtschi, Stephan J. Eidenbenz:
Deterministic Preparation of Dicke States. CoRR abs/1904.07358 (2019) - [i5]Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
Instructions' Latencies Characterization for NVIDIA GPGPUs. CoRR abs/1905.08778 (2019) - [i4]Atanu Barai, Gopinath Chennupati, Nandakishore Santhi, Abdel-Hameed A. Badawy, Stephan J. Eidenbenz:
Modeling Shared Cache Performance of OpenMP Programs using Reuse Distance. CoRR abs/1907.12666 (2019) - 2018
- [c91]Yehia Arafa, Abdel-Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
PPT-GPU: performance prediction toolkit for GPUs identifying the impact of caches: extended abstract. MEMSYS 2018: 301-302 - [c90]Patrick Crawford, Peter D. Barnes Jr., Stephan J. Eidenbenz, Philip A. Wilsey:
Sampling Simulation Model Profile Data for Analysis. SIGSIM-PADS 2018: 17-28 - [c89]Mohammad Abu Obaida, Jason Liu, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz:
Parallel Application Performance Prediction Using Analysis Based Models and HPC Simulations. SIGSIM-PADS 2018: 49-59 - [c88]Gopinath Chennupati, Stephan J. Eidenbenz, Alex Long, Olena Tkachenko, Joseph Zerr, Jason Liu:
Imcsim: Parameterized Performance Prediction for Implicit Monte Carlo codes. WSC 2018: 491-502 - [c87]Christopher Hannon, Dong Jin, Nandakishore Santhi, Stephan J. Eidenbenz, Jason Liu:
Just-in-Time Parallel simulation. WSC 2018: 640-651 - [p3]Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan, Stephan J. Eidenbenz, Nandakishore Santhi:
Synthesis of Parallel Programs on Multi-Cores. Handbook of Grammatical Evolution 2018: 289-315 - [i3]Patrick J. Coles, Stephan J. Eidenbenz, Scott Pakin, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Andrey Y. Lokhov, Alexander Malyzhenkov, David Dennis Lee Mascarenas, Susan M. Mniszewski, Balu Nadiga, Dan O'Malley, Diane Oyen, Lakshman Prasad, Randy Roberts, Philip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter Swart, Marc Vuffray, Jim Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu:
Quantum Algorithm Implementations for Beginners. CoRR abs/1804.03719 (2018) - 2017
- [c86]Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz, Sunil Thulasidasan:
AMM: Scalable Memory Reuse Model to Predict the Performance of Physics Codes. CLUSTER 2017: 649-650 - [c85]Bhargava Kalla, Nandakishore Santhi, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz:
A Probabilistic Monte Carlo Framework for Branch Prediction. CLUSTER 2017: 651-652 - [c84]Bhargava Kalla, Nandakishore Santhi, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz:
Probabilistic Monte Carlo simulations for static branch prediction. IPCCC 2017: 1-4 - [c83]Gopinath Chennupati, Nandakishore Santhi, Robert F. Bird, Sunil Thulasidasan, Abdel-Hameed A. Badawy, Satyajayant Misra, Stephan J. Eidenbenz:
A Scalable Analytical Memory Model for CPU Performance Prediction. PMBS@SC 2017: 114-135 - [c82]Kishwar Ahmed, Jason Liu, Abdel-Hameed A. Badawy, Stephan J. Eidenbenz:
A brief history of HPC simulation and future challenges. WSC 2017: 419-430 - [c81]Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz, Sunil Thulasidasan:
An analytical memory hierarchy model for performance prediction. WSC 2017: 908-919 - [c80]Patrick Crawford, Stephan J. Eidenbenz, Peter D. Barnes Jr., Philip A. Wilsey:
Some properties of communication behaviors in discrete-event simulation models. WSC 2017: 1025-1036 - 2016
- [j25]Richard J. Zamora, Arthur F. Voter, Danny Perez, Nandakishore Santhi, Susan M. Mniszewski, Sunil Thulasidasan, Stephan J. Eidenbenz:
Discrete event performance prediction of speculatively parallel temperature-accelerated dynamics. Simul. 92(12): 1065-1086 (2016) - [j24]Guillaume Chapuis, Stephan J. Eidenbenz, Nandakishore Santhi:
GPU Performance Prediction Through Parallel Discrete Event Simulation and Common Sense. EAI Endorsed Trans. Ubiquitous Environ. 3(10): e4 (2016) - [c79]Kishwar Ahmed, Jason Liu, Stephan J. Eidenbenz, Joe Zerr:
Scalable Interconnection Network Models for Rapid Performance Prediction of HPC Applications. HPCC/SmartCity/DSS 2016: 1069-1078 - [c78]Kishwar Ahmed, Mohammad Obaida, Jason Liu, Stephan J. Eidenbenz, Nandakishore Santhi, Guillaume Chapuis:
An Integrated Interconnection Network Model for Large-Scale Performance Prediction. SIGSIM-PADS 2016: 177-187 - [c77]Qiang Guan, Nathan DeBardeleben, Panruo Wu, Stephan J. Eidenbenz, Sean Blanchard, Laura Monroe, Elisabeth Baseman, Li Tan:
Design, Use and Evaluation of P-FSEFI: A Parallel Soft Error Fault Injection Framework for Emulating Soft Errors in Parallel Applications. SimuTools 2016: 9-17 - [c76]Joan Boyar, Stephan J. Eidenbenz, Lene M. Favrholdt, Michal Kotrbcík, Kim S. Larsen:
Online Dominating Set. SWAT 2016: 21:1-21:15 - [c75]Guillaume Chapuis, David Nicholaeff, Stephan J. Eidenbenz, Robert S. Pavel:
Predicting performance of Smoothed Particle Hydrodynamics codes at large scales. WSC 2016: 1825-1835 - [i2]Joan Boyar, Stephan J. Eidenbenz, Lene M. Favrholdt, Michal Kotrbcík, Kim S. Larsen:
Online Dominating Set. CoRR abs/1604.05172 (2016) - 2015
- [j23]Susan M. Mniszewski, Christoph Junghans, Arthur F. Voter, Danny Perez, Stephan J. Eidenbenz:
TADSim: Discrete Event-Based Performance Prediction for Temperature-Accelerated Dynamics. ACM Trans. Model. Comput. Simul. 25(3): 15:1-15:26 (2015) - [c74]Guillaume Chapuis, Stephan J. Eidenbenz, Nandakishore Santhi, Eunjung Park:
Simian integrated framework for parallel discrete event simulation on GPUs. WSC 2015: 1127-1138 - [c73]Eunjung Park, Stephan J. Eidenbenz, Nandakishore Santhi, Guillaume Chapuis, Bradley W. Settlemyer:
Parameterized benchmarking of parallel discrete event simulation systems: communication, computation, and memory. WSC 2015: 2836-2847 - [c72]Nandakishore Santhi, Stephan J. Eidenbenz, Jason Liu:
The simian concept: parallel discrete event simulation with interpreted languages and just-in-time compilation. WSC 2015: 3013-3024 - 2014
- [c71]Guanhua Yan, Stephan J. Eidenbenz:
Sim-Watchdog: Leveraging Temporal Similarity for Anomaly Detection in Dynamic Graphs. ICDCS 2014: 154-165 - [c70]