Titlebook: High Performance Computer Applications; 6th International Co Isidoro Gitler,Jaime Klapp Conference proceedings 2016 Springer International

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详细目录

Study of Particle Swarm Optimization Algorithms Using Message Passing Interface and Graphical Proceses of the problem can collaborate to reach a solution. Among its advantages are fast convergence, large exploration coverage, and adequate global optimization; however to address the premature convergence problem, modifications to the basic model have been developed such as Aging Leader and Challeng

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纯朴

insecticide

Parallel Meshing for Finite Element Analysisce, huge meshes. A common bottle-neck in FE calculations is domain meshing. In this paper we discuss our implementation of a parallel-meshing tool. Firstly, we create a rough mesh with a serial procedure based on a Constrained Delaunay Triangulation; secondly, such a mesh is divided into N parts via

Harpoon

Dynamic Communication-Aware Scheduling with Uncertainty of Workflow Applications in Cloudsfic workflow execution, where the job scheduling problem becomes more complex, especially when communication processes are taken into account. To provide good performance, many algorithms have been designed for distributed environments. However, these algorithms are not adapted to the uncertain and

exclusice

Structure Optimization with a Bio-inspired Methodrategy starts with a rectangular grid of elements of uniform thickness with boundary displacements and force conditions. The thickness of each element can grow or shrink depending on the internal strain, this process is done iteratively. The internal strain is found using the finite element method s

胰脏

An Agglomeration Strategy for the Parallel Processes Mapping onto a Distributed Computing Architectulel system is executed on a distributed computing architecture, communications over the network and the time spent by them become very important..This paper introduces a strategy, based on the Max-flow min-cut theorem, to agglomerate and allocate parallel processes onto a distributed computing archi

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Parallel Implementation of an Evolutionary Algorithm for Function Minimization on a GPGPUvariables. The parallel implementation was carried using the GPGPU (General-Purpose Computing on Graphics Processing Units) technique. Evolutionary programming (EP) was selected from the available evolutionary algorithm paradigms because it presents low dependency between its genetic operators. This