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Second, the DP algorithm is parallelized using a peer-to-peer parallel paradigm.
Second, conventional Gaussian mixture model learning steps are accommodated in the parallel paradigm of the MapReduce platform.
Due to their size they very often require the usage of a parallel paradigm for efficient computation.
At last, a new dynamic load balancing approach named scheduler worker parallel paradigm is proposed and evaluated.
In this work we propose to exploit the Spectral-Projected-Gradient method of optimization by its relaunching from the parallel paradigm.
The parallel paradigm aims at reducing the computation time as well as alleviating the computer memory requirement associated with running a multi-dimensional DP model.
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The work thus focuses on implementing and analyzing different parallel paradigms: multi-core parallelism, cluster parallelism and the combination of both.
As a result, different components of applications can be written in the most appropriate parallel paradigms.
We investigate three common parallel paradigms on hierarchical architectures with up to 224 cores.
NAMD2 uses a portable run-time framework called Converse that also supports interoperability among multiple parallel paradigms.
The methodology integrates theoretical and practical sections which are focused on teaching two parallel paradigms, master/Worker and SPMD.
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