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Titlebook: Euro-Par 2014: Parallel Processing Workshops; Euro-Par 2014 Intern Luís Lopes,Julius Žilinskas,Michael Alexander Conference proceedings 201

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楼主: aspirant
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Parallelizing a CAD Model Processing Tool from the Automotive Industry features as far as possible. Reasonable speedup has been achieved on a shared memory parallel architecture. Furthermore, additional potential has been located for future parallelization and optimization work.
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An Empirical Evaluation of GPGPU Performance Models matrix multiplication) to assess the efficacy and usability of a set of promising approaches. We conclude that the available GPU performance modeling solutions are very sensitive to applications and platform changes, and require significant efforts for tuning and calibration when new analyses are required.
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Parallelization of a Tridimensional Finite Element Program for Structural Behaviour Analysis the Peti concrete dam through 66 years of operation, using a finite element mesh of about 13 thousand nodes each with 3 degrees of freedom. Preliminary results are obtained using a local, distributed memory cluster and show that a significant decrease in the program’s total running time is achieved.
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Parallel Shared-Memory Multi-Objective Stochastic Search for Competitive Facility Locationst its precursor in the sense of the precision of optimization and that it has almost linear speed-up on 16 shared-memory processing units, when solving competitive facility location problems of different scope reasonable for practical applications.
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Dynamic Scheduling of MapReduce Shuffle under Bandwidth Constraints and let the implementation perform its optimizations. During the computation, there is a phase called . where every node sends a possibly large amount of data to every other node. This paper proposes and evaluates two algorithms to improve data transfers during the . phase under bandwidth constraints.
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Klaus Kraemer,Uwe H. Bittlingmayer the Peti concrete dam through 66 years of operation, using a finite element mesh of about 13 thousand nodes each with 3 degrees of freedom. Preliminary results are obtained using a local, distributed memory cluster and show that a significant decrease in the program’s total running time is achieved.
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