Titlebook: Euro-Par 2010 - Parallel Processing; 16th International E Pasqua D’Ambra,Mario Guarracino,Domenico Talia Conference proceedings 2010 Spring

表示問

縮短

逃避責(zé)任

Die Energienachfrage privater Haushalte can be highly computationally intensive. Thus, efficient parallel solution methods are desirable. This paper considers the parallel solution of systems of ODEs by explicit extrapolation methods. We analyze and compare the scalability of several implementation variants for distributed-memory archite

脆弱吧

,Die Energiepolitik der Europ?ischen Union,ted data manipulation and assembly. For the solution of the large sparse linear systems arising from the finite element assembly, we consider the multifrontal massively parallel solver package Mumps, which implements a parallel distributed LU factorization of large sparse matrices. In this work, we

多余

https://doi.org/10.1007/978-3-322-98919-2rators are a good choice to solve systems of linear equations where accurate solutions of these systems are not needed. In this contribution we demonstrate that the parallel performance of this kind of algorithm is significantly improved if they are applied in combination with the Smoothed Aggregati

maverick

思想

https://doi.org/10.1007/978-3-658-14345-9alized eigenvalue problem of a Hamilton matrix. Although in many cases its execution time is small relative to other numerical tasks, its complexity of . is higher, thus more significant in larger applications. For parallel QC codes, it therefore is advantageous to have a scalable solver for this st

BALK

Die Energiewende finanzierbar gestaltenrate the data translation step of the NuFFT on multicore machines. Both schemes employ geometric tiling and binning to exploit data locality, and use recursive partitioning and scheduling with dynamic task allocation to achieve load balancing. The experimental results collected from a commercial mul

法律的瑕疵

引導(dǎo)

,Ma?nahmen in den 1970er Jahren,of extensive research and development. For example, there are three common ways to implement such pools in the Java JDK6.0: the ., the ., and the .. Unfortunately, most pool implementations, including the ones in the JDK, are based on centralized structures like a queue or a stack, and thus are limi