Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Ki Sing Chan"'
This chapters documents the implementation of a parallel distributed memory out-of-core (OOC) solver for performing LU and Cholesky factorizations of a large dense matrix on clusters equipped with Intel® Xeon Phi™ coprocessors. The OOC solver take
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8cc6e3e566f4eaa352cb2d2416887209
https://doi.org/10.1016/b978-0-12-802118-7.00026-1
https://doi.org/10.1016/b978-0-12-802118-7.00026-1
Autor:
Mustafa AbdulJabbar, Jefferson Amstutz, Cédric Andreolli, Edoardo Aprà, Nikita Astafiev, Troy Baer, Carsten Benthin, Per Berg, Vincent Betro, Leonardo Borges, Ryan Braby, Glenn Brook, Ilya Burylov, Ki Sing Chan, Gilles Civario, Guillaume Colin de Verdière, Eduardo D’Azevedo, Jim Dempsey, Alejandro Duran, Manfred Ernst, Kerry Evans, Rob Farber, Louis Feng, Evgeny Fiksman, Jeff Hammond, Michael Hebenstreit, Christopher Hughes, Sverre Jarp, Jim Jeffers, Gregory S. Johnson, Vadim Karpusenko, Michael Klemm, Karol Kowalski, Michael Lysaght, Anton Malakhov, Tim Mattson, Simon McIntosh-Smith, Larry Meadows, Karl Meerbergen, Iosif Meyerov, Kent Milfeld, Paul Peltz, Simon John Pennycook, Jacob Weismann Poulsen, Karthik Raman, James Reinders, Alexander Reinefeld, Dirk Roose, Carlos Rosales-Fernandez, Karl Schulz, Jason Sewall, Gregg Skinner, Mikhail Smelyanskiy, Thomas Steinke, Shi-Quan Su, Alexander Sysoyev, Philippe Thierry, Antonio Valles, Jerome Vienne, Andrey Vladimirov, Ingo Wald, Florian Wende, Kwai Lam Wong, Sven Woop, Claude Wright, Rio Yokota, Charles Yount, Albert-Jan Nicholas Yzelman, Weiqun Zhang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09d22a6e27e1eb739789ab8168d3ff17
https://doi.org/10.1016/b978-0-12-802118-7.09989-1
https://doi.org/10.1016/b978-0-12-802118-7.09989-1
Autor:
James Reinders, James Jeffers
High Performance Parallelism Pearls shows how to leverage parallelism on processors and coprocessors with the same programming – illustrating the most effective ways to better tap the computational potential of systems with Intel Xeon Phi coprocess