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of 57
pro vyhledávání: '"Teranishi, Keita"'
Autor:
Valero-Lara, Pedro, Huante, Alexis, Lail, Mustafa Al, Godoy, William F., Teranishi, Keita, Balaprakash, Prasanna, Vetter, Jeffrey S.
We evaluate the use of the open-source Llama-2 model for generating well-known, high-performance computing kernels (e.g., AXPY, GEMV, GEMM) on different parallel programming models and languages (e.g., C++: OpenMP, OpenMP Offload, OpenACC, CUDA, HIP;
Externí odkaz:
http://arxiv.org/abs/2309.07103
We employ pressure point analysis and roofline modeling to identify performance bottlenecks and determine an upper bound on the performance of the Canonical Polyadic Alternating Poisson Regression Multiplicative Update (CP-APR MU) algorithm in the Sp
Externí odkaz:
http://arxiv.org/abs/2307.03276
Autor:
Godoy, William F., Valero-Lara, Pedro, Teranishi, Keita, Balaprakash, Prasanna, Vetter, Jeffrey S.
We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported pro
Externí odkaz:
http://arxiv.org/abs/2306.15121
Tensor decomposition models play an increasingly important role in modern data science applications. One problem of particular interest is fitting a low-rank Canonical Polyadic (CP) tensor decomposition model when the tensor has sparse structure and
Externí odkaz:
http://arxiv.org/abs/2012.01520
Autor:
Agullo, Emmanuel, Altenbernd, Mirco, Anzt, Hartwig, Bautista-Gomez, Leonardo, Benacchio, Tommaso, Bonaventura, Luca, Bungartz, Hans-Joachim, Chatterjee, Sanjay, Ciorba, Florina M., DeBardeleben, Nathan, Drzisga, Daniel, Eibl, Sebastian, Engelmann, Christian, Gansterer, Wilfried N., Giraud, Luc, Goeddeke, Dominik, Heisig, Marco, Jezequel, Fabienne, Kohl, Nils, Li, Xiaoye Sherry, Lion, Romain, Mehl, Miriam, Mycek, Paul, Obersteiner, Michael, Quintana-Orti, Enrique S., Rizzi, Francesco, Ruede, Ulrich, Schulz, Martin, Fung, Fred, Speck, Robert, Stals, Linda, Teranishi, Keita, Thibault, Samuel, Thoennes, Dominik, Wagner, Andreas, Wohlmuth, Barbara
This work is based on the seminar titled ``Resiliency in Numerical Algorithm Design for Extreme Scale Simulations'' held March 1-6, 2020 at Schloss Dagstuhl, that was attended by all the authors. Naive versions of conventional resilience techniques w
Externí odkaz:
http://arxiv.org/abs/2010.13342
Akademický článek
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Akademický článek
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In the presence of accelerated fault rates, which are projected to be the norm on future exascale systems, it will become increasingly difficult for high-performance computing (HPC) applications to accomplish useful computation. Due to the fault-obli
Externí odkaz:
http://arxiv.org/abs/1610.01728
Autor:
Teranishi, Keita
Thesis (Ph.D.)--Pennsylvania State University, 2004.
Mode of access: World Wide Web.
Mode of access: World Wide Web.
Deploying scientific computing software for high performance computing (HPC) systems has become increasingly challenging with the rapid growth of the HPC software stack to accommodate a variety of application needs to exploit ever-increasing computin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2515d5593190101d7d6d79300dce2b7e