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The results show that with the increase of processor number, the distributed ICA can significantly shorten the simulation time.
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The calculation shows that with the increased amount of processor computing time has significantly reduced.
There is a growing demand of low power design, and the increasing demand of processor performance improvements leads to deeper pipelines in processor design points.
The processing time for climate data decreased with the increasing number of processor cores when the features of parallel processing were used for the CDSL.
With the increasing number of processor cores available in modern computing architectures, task or data parallelism is required to maximally exploit the available hardware and achieve optimal processing speed.
In all reported cases the efficiency lowers with increasing number of processors and increases with the number of nodes.
In parallel processing, performance is expected to increase in the same proportion as the increase in number of processor cores.
As computers are built with increasing numbers of processors, torus performance can still be made comparable to the hypercube by gradually increasing the dimension of the interconnect.
The tests demonstrate that CR-OLAP scales well with increasing number of processors, even for complex queries.
Numerical results are reported on different types of randomly generated instances, using an increasing number of processors and different distributions of processes between SS and VND.
Results of the experiments performed under high contention show that the performance of our implementation scales linearly with increasing number of processors.
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CEO of Professional Science Editing for Scientists @ prosciediting.com