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Publication search results
found 1,216 matches
- 2024
- Jesús Carretero, Estela Suarez, Martin Schulz:
Malleability techniques applications in high-performance computing. Int. J. High Perform. Comput. Appl. 38(2): 53-54 (2024) - Alberto Cascajo, David E. Singh, Jesús Carretero:
Detecting interference between applications and improving the scheduling using malleable application clones. Int. J. High Perform. Comput. Appl. 38(2): 108-133 (2024) - Joel Criado, Victor Lopez, Joan Vinyals-Ylla-Catala, Guillem Ramirez-Miranda, Xavier Teruel, Marta Garcia-Gasulla:
Role-shifting threads: Increasing OpenMP malleability to address load imbalance at MPI and OpenMP. Int. J. High Perform. Comput. Appl. 38(2): 94-107 (2024) - Roman Iakymchuk, Stef Graillat, José Ignacio Aliaga:
General framework for re-assuring numerical reliability in parallel Krylov solvers: A case of bi-conjugate gradient stabilized methods. Int. J. High Perform. Comput. Appl. 38(1): 17-33 (2024) - Daniel Langr, Tomás Dytrych:
Parallel multithreaded deduplication of data sequences in nuclear structure calculations. Int. J. High Perform. Comput. Appl. 38(1): 5-16 (2024) - Iker Martín-Álvarez, José Ignacio Aliaga, Maribel Castillo, Sergio Iserte, Rafael Mayo:
Dynamic spawning of MPI processes applied to malleability. Int. J. High Perform. Comput. Appl. 38(2): 69-93 (2024) - Daniil Pavlov, Vladislav Galigerov, Daniil Kolotinskii, Vsevolod P. Nikolskiy, Vladimir V. Stegailov:
GPU-based molecular dynamics of fluid flows: Reaching for turbulence. Int. J. High Perform. Comput. Appl. 38(1): 34-49 (2024) - Rafael Rodríguez-Sánchez, Adrián Castelló, Sandra Catalán, Francisco D. Igual, Enrique S. Quintana-Ortí:
Experiences with nested parallelism in task-parallel applications using malleable BLAS on multicore processors. Int. J. High Perform. Comput. Appl. 38(2): 55-68 (2024) - Roman Wyrzykowski, Ewa Deelman:
Guest Editor's note: Special issue on challenges and solutions for porting applications to next-generation high performance computing systems. Int. J. High Perform. Comput. Appl. 38(1): 3-4 (2024) - 2023
- Sadaf R. Alam, Miguel Gila, Mark Klein, Maxime Martinasso, Thomas C. Schulthess:
Versatile software-defined HPC and cloud clusters on Alps supercomputer for diverse workflows. Int. J. High Perform. Comput. Appl. 37(3-4): 288-305 (2023) - José Ignacio Aliaga, Hartwig Anzt, Thomas Grützmacher, Enrique S. Quintana-Ortí, Andrés E. Tomás:
Compressed basis GMRES on high-performance graphics processing units. Int. J. High Perform. Comput. Appl. 37(2): 82-100 (2023) - He Bai, Changjun Hu, Yuhan Zhu, Dandan Chen, Genshen Chu, Shuai Ren:
Accelerating cluster dynamics simulation of fission gas behavior in nuclear fuel on deep computing unit-based heterogeneous architecture supercomputer. Int. J. High Perform. Comput. Appl. 37(5): 516-529 (2023) - Parantapa Bhattacharya, Jiangzhuo Chen, Stefan Hoops, Dustin Machi, Bryan L. Lewis, Srinivasan Venkatramanan, Mandy L. Wilson, Brian Klahn, Aniruddha Adiga, Benjamin Hurt, Joseph Outten, Abhijin Adiga, Andrew S. Warren, Young Yun Baek, Przemyslaw J. Porebski, Achla Marathe, Dawen Xie, Samarth Swarup, Anil Vullikanti, Henning S. Mortveit, Stephen G. Eubank, Christopher L. Barrett, Madhav Vinayak Marathe:
Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support. Int. J. High Perform. Comput. Appl. 37(1): 4-27 (2023) - Sanjukta Bhowmick, Patrick Bell, Michela Taufer:
A Survey of Graph Comparison Methods with Applications to Nondeterminism in High-Performance Computing. Int. J. High Perform. Comput. Appl. 37(3-4): 306-327 (2023) - Noel Chalmers, Abhishek Mishra, Damon McDougall, Tim Warburton:
HipBone: A performance-portable graphics processing unit-accelerated C++ version of the NekBone benchmark. Int. J. High Perform. Comput. Appl. 37(5): 560-577 (2023) - Jie Chen, Zhiwei Nie, Yu Wang, Kai Wang, Fan Xu, Zhiheng Hu, Bing Zheng, Zhennan Wang, Guoli Song, Jingyi Zhang, Jie Fu, Xiansong Huang, Zhongqi Wang, Zhixiang Ren, Qiankun Wang, Daixi Li, Dongqing Wei, Bin Zhou, Chao Yang, Yonghong Tian:
Running ahead of evolution - AI-based simulation for predicting future high-risk SARS-CoV-2 variants. Int. J. High Perform. Comput. Appl. 37(6): 650-665 (2023) - Edmond Chow:
Editorial. Int. J. High Perform. Comput. Appl. 37(6): 649 (2023) - John M. Dennis, Allison H. Baker, Brian Dobbins, Michael M. Bell, Jian Sun, Youngsung Kim, Ting-Yu Cha:
Enabling efficient execution of a variational data assimilation application. Int. J. High Perform. Comput. Appl. 37(2): 101-114 (2023) - Abigail C. Dommer, Lorenzo Casalino, Fiona L. Kearns, Mia Rosenfeld, Nicholas Wauer, Surl-Hee Ahn, John Russo, A. Sofia F. Oliveira, Clare Morris, Anthony T. Bogetti, Anda Trifan, Alexander Brace, Terra Sztain, Austin Clyde, Heng Ma, S. Chakra Chennubhotla, Hyungro Lee, Matteo Turilli, Syma Khalid, Teresa Tamayo-Mendoza, Matthew Welborn, Anders S. Christensen, Daniel G. A. Smith, Zhuoran Qiao, Sai K. Sirumalla, Michael O'Connor, Frederick R. Manby, Anima Anandkumar, David J. Hardy, James C. Phillips, Abraham C. Stern, Josh Romero, David Clark, Mitchell Dorrell, Tom Maiden, Lei Huang, John D. McCalpin, Christopher J. Woods, Alan Gray, Matt Williams, Bryan Barker, Harinda Rajapaksha, Richard Pitts, Tom Gibbs, John E. Stone, Daniel M. Zuckerman, Adrian J. Mulholland, Thomas F. Miller III, Shantenu Jha, Arvind Ramanathan, Lillian T. Chong, Rommie E. Amaro:
#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. Int. J. High Perform. Comput. Appl. 37(1): 28-44 (2023) - Jack J. Dongarra, Bernard Tourancheau:
Guest editors note: Special issue on clusters, clouds, and data for scientific computing. Int. J. High Perform. Comput. Appl. 37(3-4): 211-212 (2023) - Lukas Einkemmer, Alexander Moriggl:
Semi-Lagrangian 4d, 5d, and 6d kinetic plasma simulation on large-scale GPU-equipped supercomputers. Int. J. High Perform. Comput. Appl. 37(2): 180-196 (2023) - Jorge Ejarque, Rosa M. Badia:
Automatizing the creation of specialized high-performance computing containers. Int. J. High Perform. Comput. Appl. 37(3-4): 272-287 (2023) - Marc T. Henry de Frahan, Jon S. Rood, Marcus S. Day, Hariswaran Sitaraman, Shashank Yellapantula, Bruce A. Perry, Ray W. Grout, Ann S. Almgren, Weiqun Zhang, John B. Bell, Jacqueline H. Chen:
PeleC: An adaptive mesh refinement solver for compressible reacting flows. Int. J. High Perform. Comput. Appl. 37(2): 115-131 (2023) - Megan Hickman Fulp, Dakota Fulp, Changfeng Zou, Cooper Sanders, Ayan Biswas, Melissa C. Smith, Jon C. Calhoun:
Accelerated dynamic data reduction using spatial and temporal properties. Int. J. High Perform. Comput. Appl. 37(5): 539-559 (2023) - Marc González, Enric Morancho:
Heterogeneous programming using OpenMP and CUDA/HIP for hybrid CPU-GPU scientific applications. Int. J. High Perform. Comput. Appl. 37(5): 626-646 (2023) - Philipp Grete, Joshua C. Dolence, Jonah M. Miller, Joshua Brown, Ben Ryan, Andrew Gaspar, Forrest Wolfgang Glines, Sriram Swaminarayan, Jonas Lippuner, Clell J. Solomon, Galen M. Shipman, Christoph Junghans, Daniel Holladay, James M. Stone, Luke F. Roberts:
Parthenon - a performance portable block-structured adaptive mesh refinement framework. Int. J. High Perform. Comput. Appl. 37(5): 465-486 (2023) - Darren J. Hsu, Hao Lu, Aditya Kashi, Michael A. Matheson, John Gounley, Feiyi Wang, Wayne Joubert, Jens Glaser:
TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences. Int. J. High Perform. Comput. Appl. 37(6): 666-682 (2023) - Sergio Iserte, Alejandro González-Barberá, Paloma Barreda, Krzysztof Rojek:
A study on the performance of distributed training of data-driven CFD simulations. Int. J. High Perform. Comput. Appl. 37(5): 503-515 (2023) - Emmanuel Jeannot, Guillaume Pallez, Nicolas Vidal:
IO-aware Job-Scheduling: Exploiting the Impacts of Workload Characterizations to select the Mapping Strategy. Int. J. High Perform. Comput. Appl. 37(3-4): 213-228 (2023) - Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Mariam Kiran, Ewa Deelman, Prasanna Balaprakash:
Graph neural networks for detecting anomalies in scientific workflows. Int. J. High Perform. Comput. Appl. 37(3-4): 394-411 (2023)
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