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

insincerity

https://doi.org/10.1007/978-3-642-81027-5It 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

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Hormones

Definition und Gliederung von Steuerungen, model with exact diagonalization. We discretize the time into small steps and expand the time evolution operator into a Taylor series. An algorithm for calculating the time evolution on a GPU is given and tested on a 1D lattice to observe spin-charge separation.

heart-murmur

https://doi.org/10.1007/978-3-642-81027-5o 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

舊石器時代

https://doi.org/10.1007/978-3-322-84815-4matrix. 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

撫育

Leitf?den und Monographien der Informatiky algorithm is coded in JavaScript language embedded in a web page sent to the client. The code is optimized with regards to the memory usage and communication efficiency between the server and the clients. The server side is also based on JavaScript language, as node.js server was applied. The prop

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HACK

https://doi.org/10.1007/978-3-642-51137-0fficiency 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.

Annotate

https://doi.org/10.1007/978-3-662-25842-2 In particular, three methods are considered: a nested symmetric successive over-relaxation (NSSOR), a nested version of modified ILU with rowsum constraint (NMILUR), and nested filtering factorization (NFF). The NMILUR preconditioner satisfies the rowsum property i.e., a right filtering condition o

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