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The presented paper deals with possible approaches to parallel implementation of solution of a hyper-dimensional dynamical particle system.
In this paper we investigate new approaches to parallel lossless lightweight compression methods based on fixed-length minimum bit encoding for GPU processors.
In this paper, two approaches to parallel GPU evaluation of the Permutation Flowshop Scheduling Problem, with makespan and total flowtime criteria, are proposed.
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This paper presents an approach to parallel implementation of wavelet transforms in a distributed computing environment.
The result is a new approach to parallel programming that addresses correctness and openness in a unique way.
Also, we introduce a novel, extremely efficient approach to parallel data filtering, and show that our algorithms scale super-linearly on multi-core clusters.
With the advent of the Compute Unified Device Architecture (CUDA), modern graphics processing units (GPUs) provide an alternative approach to parallel computing for scientific simulations.
Now that multicore chips are common, providing an approach to parallel programming that is usable by regular programmers has become even more important.
A current approach to parallel software development is the use of analysis or visualisation tools to reveal important aspects of the parallel execution, often by post-execution analysis of trace files.
We investigate Hash-Distributed A⁎ (HDA⁎), a simple approach to parallel best-first search that asynchronously distributes and schedules work among processors based on a hash function of the search state.
Therefore, a proteomic isotope-coded approach to parallel, quantitative analysis of cysteome S-nitrosylation and S-oxidation was developed.
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