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ORCIDInternational Journal of High Performance Computing Applications, Volume 35
Volume 35, Number 1, January 2021
- Roman Wyrzykowski
, Ewa Deelman:
Guest editor's note: Special issue on application performance optimization in the era of extreme heterogeneity.
- Dominik Ernst, Georg Hager, Jonas Thies, Gerhard Wellein:
Performance engineering for real and complex tall & skinny matrix multiplication kernels on GPUs. - Krzysztof Jurczuk, Marcin Czajkowski, Marek Kretowski:
Fitness evaluation reuse for accelerating GPU-based evolutionary induction of decision trees. - Krzysztof Rojek, Kamil Halbiniak, Lukasz Kuczynski:
CFD code adaptation to the FPGA architecture.
- Hannah Morgan, Patrick Sanan, Matthew G. Knepley, Richard Tran Mills:
Understanding performance variability in standard and pipelined parallel Krylov solvers. - Andreas Pieper, Georg Hager, Holger Fehske:
A domain-specific language and matrix-free stencil code for investigating electronic properties of Dirac and topological materials. - Yutong Ye, Hongyin Zhu, Chaoying Zhang, Binghai Wen:
Efficient graphic processing unit implementation of the chemical-potential multiphase lattice Boltzmann method. - Bartosz Kohnke, Carsten Kutzner, Andreas Beckmann, Gert Lube, Ivo Kabadshow, Holger Dachsel, Helmut Grubmüller:
A CUDA fast multipole method with highly efficient M2L far field evaluation.
Volume 35, Number 2, March 2021
- Wenpeng Ma, Xiao-Chuan Cai:
Point-block incomplete LU preconditioning with asynchronous iterations on GPU for multiphysics problems. - Ross Adelman:
Highly parallel boundary element method for solving extremely large, wide-area power-line models. - Weijian Zheng, Dali Wang, Fengguang Song:
Designing a parallel Feel-the-Way clustering algorithm on HPC systems. - Vedran Novakovic, Sanja Singer:
Implicit Hari-Zimmermann algorithm for the generalized SVD on the GPUs.
Volume 35, Number 3, May 2021
- Peter Benner, Enrique S. Quintana-Ortí, Jens Saak:
Introduction to the Special Issue related to the Power-Aware Computing Workshop 2019 - PACO 2019.
- Jonas Dünnebacke, Stefan Turek, Christoph Lohmann, Andriy Sokolov, Peter Zajac:
Increased space-parallelism via time-simultaneous Newton-multigrid methods for nonstationary nonlinear PDE problems. - Pratik Nayak, Terry Cojean, Hartwig Anzt:
Evaluating asynchronous Schwarz solvers on GPUs. - Axel Klawonn, Martin Lanser, Oliver Rheinbach, Gerhard Wellein, Markus Wittmann:
Energy efficiency of nonlinear domain decomposition methods. - Ernesto Dufrechou, Pablo Ezzatti, Enrique S. Quintana-Ortí:
Selecting optimal SpMV realizations for GPUs via machine learning. - Maria Barreda, Manuel F. Dolz, M. Asunción Castaño:
Convolutional neural nets for estimating the run time and energy consumption of the sparse matrix-vector product.
Volume 35, Number 4, July 2021
- Tommaso Benacchio, Luca Bonaventura, Mirco Altenbernd, Chris D. Cantwell, Peter D. Düben, Mike Gillard, Luc Giraud, Dominik Göddeke, Erwan Raffin, Keita Teranishi, Nils Wedi:
Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction. - Nikolay Kondratyuk, Vsevolod P. Nikolskiy, Daniil Pavlov, Vladimir V. Stegailov:
GPU-accelerated molecular dynamics: State-of-art software performance and porting from Nvidia CUDA to AMD HIP. - Hatem Elshazly, Francesc Lordan, Jorge Ejarque, Rosa M. Badia:
Accelerated execution via eager-release of dependencies in task-based workflows. - Ahmad Abdelfattah, Hartwig Anzt, Erik G. Boman, Erin C. Carson, Terry Cojean, Jack J. Dongarra, Alyson Fox, Mark Gates, Nicholas J. Higham, Xiaoye S. Li, Jennifer A. Loe, Piotr Luszczek, Srikara Pranesh, Siva Rajamanickam, Tobias Ribizel, Barry F. Smith, Kasia Swirydowicz, Stephen J. Thomas, Stanimire Tomov, Yaohung M. Tsai, Ulrike Meier Yang:
A survey of numerical linear algebra methods utilizing mixed-precision arithmetic. - Karl-Robert Wichmann, Martin Kronbichler, Rainald Löhner, Wolfgang A. Wall:
A runtime based comparison of highly tuned lattice Boltzmann and finite difference solvers. - Shu-Mei Tseng, Bogdan Nicolae, Franck Cappello, Aparna Chandramowlishwaran:
Demystifying asynchronous I/O Interference in HPC applications. - Markus Holzer, Martin Bauer, Harald Köstler, Ulrich Rüde:
Highly efficient lattice Boltzmann multiphase simulations of immiscible fluids at high-density ratios on CPUs and GPUs through code generation.
Volume 35, Number 5, September 2021
- Bronis R. de Supinski:
Special Issue Introduction: The Gordon Bell Special Prize for HPC-Based COVID-19 Research Finalists.
- Lorenzo Casalino, Abigail C. Dommer, Zied Gaieb, Emília P. Barros, Terra Sztain, Surl-Hee Ahn, Anda Trifan, Alexander Brace, Anthony T. Bogetti, Austin Clyde, Heng Ma, Hyungro Lee, Matteo Turilli, Syma Khalid, Lillian T. Chong, Carlos Simmerling, David J. Hardy, Julio D. C. Maia, James C. Phillips, Thorsten Kurth, Abraham C. Stern, Lei Huang, John D. McCalpin, Mahidhar Tatineni, Tom Gibbs, John E. Stone, Shantenu Jha, Arvind Ramanathan, Rommie E. Amaro:
AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. - Jens Glaser, Josh Vincent Vermaas, David M. Rogers, Jeff Larkin, Scott LeGrand, Swen Boehm, Matthew B. Baker, Aaron Scheinberg, Andreas F. Tillack, Mathialakan Thavappiragasam, Ada Sedova, Oscar R. Hernandez:
High-throughput virtual laboratory for drug discovery using massive datasets. - 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:
Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models. - Jonathan Ozik, Justin M. Wozniak, Nicholson T. Collier, Charles M. Macal, Mickaël Binois:
A population data-driven workflow for COVID-19 modeling and learning.
Volume 35, Number 6, November 2021
- Timothy C. Germann:
Co-design in the Exascale Computing Project. 503-507 - Weiqun Zhang, Andrew Myers, Kevin Gott, Ann S. Almgren, John B. Bell:
AMReX: Block-structured adaptive mesh refinement for multiphysics applications. 508-526 - 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:
Efficient exascale discretizations: High-order finite element methods. 527-552 - 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. 553-571 - Susan M. Mniszewski, James F. Belak, Jean-Luc Fattebert, Christian F. A. Negre, Stuart R. Slattery, Adetokunbo A. Adedoyin, Robert F. Bird, Choong-Seock Chang, Guangye Chen, Stéphane Ethier, Shane Fogerty, Salman Habib, Christoph Junghans, Damien Lebrun-Grandié, Jamaludin Mohd-Yusof, Stan G. Moore, Daniel Osei-Kuffuor, Steven J. Plimpton, Adrian Pope, Samuel Temple Reeve, Lee F. Ricketson, Aaron Scheinberg, Amil Y. Sharma, Michael E. Wall:
Enabling particle applications for exascale computing platforms. 572-597 - Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishniah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon:
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). 598-616 - Ian T. Foster, Mark Ainsworth, Julie Bessac, Franck Cappello, Jong Choi, Sheng Di, Zichao Wendy Di, Ali Murat Gok, Hanqi Guo, Kevin A. Huck, Christopher Kelly, Scott Klasky, Kerstin Kleese van Dam, Xin Liang, Kshitij Mehta, Manish Parashar, Tom Peterka, Line Pouchard, Tong Shu, Ozan Tugluk, Hubertus Van Dam, Lipeng Wan, Matthew Wolf, Justin M. Wozniak, Wei Xu, Igor Yakushin, Shinjae Yoo, Todd S. Munson:
Online data analysis and reduction: An important Co-design motif for extreme-scale computers. 617-635
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