Zobrazeno 1 - 10
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pro vyhledávání: '"DONGARRA, JACK"'
Autor:
Hoefler, Torsten, Copik, Marcin, Beckman, Pete, Jones, Andrew, Foster, Ian, Parashar, Manish, Reed, Daniel, Troyer, Matthias, Schulthess, Thomas, Ernst, Dan, Dongarra, Jack
HPC and Cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent access to comput
Externí odkaz:
http://arxiv.org/abs/2401.04552
Publikováno v:
ACM Trans. Math. Softw. October 2024.
Parker and L\^e introduced random butterfly transforms (RBTs) as a preprocessing technique to replace pivoting in dense LU factorization. Unfortunately, their FFT-like recursive structure restricts the dimensions of the matrix. Furthermore, on multi-
Externí odkaz:
http://arxiv.org/abs/2312.09376
Autor:
Murray, Riley, Demmel, James, Mahoney, Michael W., Erichson, N. Benjamin, Melnichenko, Maksim, Malik, Osman Asif, Grigori, Laura, Luszczek, Piotr, Dereziński, Michał, Lopes, Miles E., Liang, Tianyu, Luo, Hengrui, Dongarra, Jack
Randomized numerical linear algebra - RandNLA, for short - concerns the use of randomization as a resource to develop improved algorithms for large-scale linear algebra computations. The origins of contemporary RandNLA lay in theoretical computer sci
Externí odkaz:
http://arxiv.org/abs/2302.11474
Autor:
Demmel, James, Dongarra, Jack, Gates, Mark, Henry, Greg, Langou, Julien, Li, Xiaoye, Luszczek, Piotr, Pereira, Weslley, Riedy, Jason, Rubio-González, Cindy
Numerical exceptions, which may be caused by overflow, operations like division by 0 or sqrt(-1), or convergence failures, are unavoidable in many cases, in particular when software is used on unforeseen and difficult inputs. As more aspects of socie
Externí odkaz:
http://arxiv.org/abs/2207.09281
The world of computing is in rapid transition, now dominated by a world of smartphones and cloud services, with profound implications for the future of advanced scientific computing. Simply put, high-performance computing (HPC) is at an important inf
Externí odkaz:
http://arxiv.org/abs/2203.02544
Autor:
Kolev, Tzanio, Fischer, Paul, Min, Misun, Dongarra, Jack, Brown, Jed, Dobrev, Veselin, Warburton, Tim, Tomov, Stanimire, Shephard, Mark S., Abdelfattah, Ahmad, Barra, Valeria, Beams, Natalie, Camier, Jean-Sylvain, Chalmers, Noel, Dudouit, Yohann, Karakus, Ali, Karlin, Ian, Kerkemeier, Stefan, Lan, Yu-Hsiang, Medina, David, Merzari, Elia, Obabko, Aleksandr, Pazner, Will, Rathnayake, Thilina, Smith, Cameron W., Spies, Lukas, Swirydowicz, Kasia, Thompson, Jeremy, Tomboulides, Ananias, Tomov, Vladimir
Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating p
Externí odkaz:
http://arxiv.org/abs/2109.04996
Autor:
Archibald, Rick, Chow, Edmond, D'Azevedo, Eduardo, Dongarra, Jack, Eisenbach, Markus, Febbo, Rocco, Lopez, Florent, Nichols, Daniel, Tomov, Stanimire, Wong, Kwai, Yin, Junqi
This paper presents some of the current challenges in designing deep learning artificial intelligence (AI) and integrating it with traditional high-performance computing (HPC) simulations. We evaluate existing packages for their ability to run deep l
Externí odkaz:
http://arxiv.org/abs/2011.11188
The GMRES method is used to solve sparse, non-symmetric systems of linear equations arising from many scientific applications. The solver performance within a single node is memory bound, due to the low arithmetic intensity of its computational kerne
Externí odkaz:
http://arxiv.org/abs/2011.01850
Autor:
Abdelfattah, Ahmad, Anzt, Hartwig, Boman, Erik G., Carson, Erin, Cojean, Terry, Dongarra, Jack, Gates, Mark, Grützmacher, Thomas, Higham, Nicholas J., Li, Sherry, Lindquist, Neil, Liu, Yang, Loe, Jennifer, Luszczek, Piotr, Nayak, Pratik, Pranesh, Sri, Rajamanickam, Siva, Ribizel, Tobias, Smith, Barry, Swirydowicz, Kasia, Thomas, Stephen, Tomov, Stanimire, Tsai, Yaohung M., Yamazaki, Ichitaro, Yang, Urike Meier
Within the past years, hardware vendors have started designing low precision special function units in response to the demand of the Machine Learning community and their demand for high compute power in low precision formats. Also the server-line pro
Externí odkaz:
http://arxiv.org/abs/2007.06674
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