Titlebook: Algorithms and Architectures for Parallel Processing; 13th International C Rocco Aversa,Joanna Kołodziej,Giancarlo Fortino Conference proce

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W. Meyer zur Capellen,A. Leitnerhighly tuned libraries, or orchestrated by a runtime) exert on the performance-power-energy trade-off of dense linear algebra routines. The algorithm employed for this analysis is matrix inversion via Gauss-Jordan elimination, but the results from the evaluation carry beyond this particular operatio

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https://doi.org/10.1007/978-3-662-38088-8 million nodes; for instance China’s Tianhe-2. To cope with this huge number of cores, many interconnection networks have been proposed in the literature. However, in most cases, proposed topologies have shown gaps preventing these topologies from being actually implemented and manufactured. In this

Exposition

Ch. Bouché,W. Hofmann,K.-A. Ebert,G. Köhlerand task scheduling in a heterogeneous environment such as cloud are difficult problems. Approaches for scheduling and data placement is often highly correlated, which take into account a few factors at the same time, and what are the most often adapted to applications data medium and therefore goes

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W. Meyer zur Capellen,A. Leitneren variants of this algorithm are implemented on distributed-memory computers, the synchronization time spent in computing dot products is increasingly limiting the parallel scalability. The goal of .-step algorithms is to reduce the harmful influence of dot products on the parallel performance by g

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F. Sass (Professor),Ch. Bouché (Direktor)stems in regards their services is an important indicator that reflect quality of IT resource management. In this paper, we address a reliability issue in the context of resource allocation that aims to improve performance of the distributed systems. We propose a heuristic scheduling by integrating

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Dubbel: Taschenbuch für den Maschinenbau resources. We have been developing a run-time system for this problem on PGAS language named XcalableMP-dev/StarPU [1]. Through the development, we found the necessity of adaptive load balancing for GPU/CPU work sharing to achieve the best performance for various application codes..In this paper, w

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