Titlebook: Euro-Par 2016: Parallel Processing Workshops; Euro-Par 2016 Intern Frédéric Desprez,Pierre-Fran?ois Dutot,Josef Weide Conference proceeding

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Indict

機(jī)械

https://doi.org/10.1007/978-3-7091-9998-5speed up may be reached on a multi-GPU platform (relatively to the mono-GPU case) and, as a very preliminary but promising result, that the approach can be effectively used to handle heterogenous architectures composed of a multicore chip and multiple GPUs. We expect that these results will pave the

ALTER

Die Festigkeitseigenschaften des Magnesiums,available cores) possibly enhanced with GPUs. We illustrate our discussion with the . sparse hybrid solver relying on the . and . dense and sparse direct libraries, respectively. Interestingly, this two-level MPI+task design furthermore provides extra flexibility for controlling the number of subdom

美色花錢(qián)

antecedence

Die Eisenbahntarife. Allgemeines,e meta programming techniques to synthesize multiple versions of a parallel task during the compilation process..To demonstrate its effectiveness, we evaluate the impact of our approach on the performance of a series of eight task parallel benchmarks. For those, our approach achieves substantial spe

antecedence

Quellen-und Literaturverzeichnis,ation and discuss the potential and limits of this approach in terms of productivity and effectiveness in comparison with more common parallelization techniques. Although at an early stage of development, preliminary results show the potential of the parallel programming model that we investigate in

誤傳

charisma

Experiences with Teaching a Second Year Distributed Computing Courseely: trade-offs, failures, concurrency and synchronization, performance. The paper presents the details of this approach arguing that the use of suitable abstractions allows for a rewarding learning experience that helps students familiarize with and appreciate the challenges of distributed computin

莎草

Distributed In-GPU Data Cache for Document-Oriented Data Store via PCIe over 10?Gbit Ethernetpression match query throughput with up?to three NVIDIA GeForce GTX 980 devices connected to a host via PCIe over 10?GbE. We demonstrate that the communication overhead of remote GPU devices is small and can be compensated by a great flexibility to add more GPU devices via a network. We also show th