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Titlebook: Applied Parallel and Scientific Computing; 11th International C Pekka Manninen,Per ?ster Conference proceedings 2013 Springer-Verlag Berlin

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樓主: Guffaw
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發(fā)表于 2025-3-28 17:30:33 | 只看該作者
42#
發(fā)表于 2025-3-28 22:46:29 | 只看該作者
PCJ - New Approach for Parallel Computations in JavaIt hides communication details and therefore it is easy to use and allows for fast development of parallel programs. With the PCJ user can focus on implementation of the algorithm rather than on thread or network programming. The design details with examples of usage for basic operations are describ
43#
發(fā)表于 2025-3-29 01:36:21 | 只看該作者
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發(fā)表于 2025-3-29 03:40:44 | 只看該作者
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發(fā)表于 2025-3-29 07:40:13 | 只看該作者
Parallel Numerical Simulation of Seismic Waves Propagation with Intel Math Kernel Libraryo time. The main advantages of the transform are a definite sign of the spatial part of the operator and its independence of the parameter of separation. This property allows one to efficiently organize parallel computations by means of decomposition of the computational domain with successive appli
46#
發(fā)表于 2025-3-29 14:40:16 | 只看該作者
Blocked Schur Algorithms for Computing the Matrix Square Rootmatrix. We show that by using either standard blocking or recursive blocking the computation of the square root of the triangular matrix can be made rich in matrix multiplication. Numerical experiments making appropriate use of level 3 BLAS show significant speedups over the point algorithm, both in
47#
發(fā)表于 2025-3-29 19:33:01 | 只看該作者
48#
發(fā)表于 2025-3-29 22:52:11 | 只看該作者
Use of Direct Solvers in TFETI Massively Parallel Implementationblems related to the application of an unassembled system matrix (subdomain problems’ solutions and projector application in dual operator) are solved directly. The paper deals with the comparison of the direct solvers available in PETSc on the Cray XE6 machine HECToR (PETSc, MUMPS, SuperLU) regardi
49#
發(fā)表于 2025-3-30 03:16:18 | 只看該作者
Parallel Implementation of the Sherman-Morrison Matrix Inverse Algorithmfficiency in memory and runtime on multicore CPU and GPU-equipped computers. Our methods are shown to be much more efficient than the direct method to compute the inverse of a nonsingular dense matrix, yielding up to 12 times faster performance on the CPU.
50#
發(fā)表于 2025-3-30 06:47:53 | 只看該作者
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