parallelizing


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Related to parallelizing: Parallelizing compiler, Parallelisation

parallelizing

To generate instructions for a parallel processing computer. See parallel computing.
References in periodicals archive ?
To see the benefit of parallelism, it is important to know how much speed gain is achieved by parallelizing a program over a sequential implementation.
By parallelizing conventional NMF, PNMF can achieve the same representation ability, while reducing the time complexity.
In this paper it has been made an in depth analysis of the key aspects that carry significant weight when deciding to parallelize a certain part of an application: the analysis phase of the application that is about to be parallelized; the amount of time involved to achieve the implementation; the feasibility of parallelizing the source code; situations when one should aim for central processing units optimization techniques that yield better performance on sequential source code rather than parallelizing the whole algorithm.
From the results in Section 4, we can note that when parallelizing the Quick Search algorithm by using OpenMP directive under multi-core environment, the parallel program shows better performance compared to the sequential program in terms of execution time when using different data types with different patterns length.
"Instead they are looking to their service providers for assistance in parallelizing their code for optimum performance".
However, for some domains, the number of possible parses is necessarily quite large, and this was one of the prime motivators for exploring the possibilities for parallelizing ELEXIR.
By parallelizing the solve process, including the existing efficient particle tracking algorithms, the parallel processing version of the 3D Space Charge module can shorten simulation run-times significantly.
8) If work involves much I/O it is not suitable for parallelizing because I/O operations take nearly 10X more time than any operation;
Fujitsu Laboratories has used a new "look-ahead" architecture in the circuit that compensates for quality degradation in incoming signals, parallelizing the processing and increasing the operating frequency for the circuit in order to double its speed.
Recently, many researchers are attracted to the topic of parallelizing video processing with multicore or many-core architecture, especially on the GPU-based systems [8-12,20-27].
In this paper, we have investigated the problem of parallelizing random network coding for embedded sensor systems with multicore processors.
We compared the performance of IMTP with 2D-Wave without parallelizing the entropy decoding and MT-SEP, which only parallelized the entropy decoding on a multi-core system.