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However, the data transfer between GPUs bottlenecks the efficiency of the simulations on such systems.
The efficiency of the simulations is tested in each case by imposing diffusion-controlled conditions so as to examine situations which enhance the intrinsic difficulties of the problems.
The elevated temperature was also chosen to increase the computational efficiency of the simulations, due to the increase in ion mobility and proton diffusion at this temperature, without affecting the significance of the results.
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The efficiency of the simulation is governed by the correlation between the simulated Markov chain samples.
In order to improve the computational efficiency of the simulation algorithm, we introduced two optimizations.
Unfortunately, the efficiency of the simulation decreases if the assumption breaks.
Each discrete step replaces many smaller Monte Carlo steps, thus improving the efficiency of the simulation.
Each discrete step replaces many small Monte Carlo steps, thus increasing the efficiency of the simulation.
Hence, the equivalent model of the WF needs to be built to improve the efficiency of the simulation [2].
Distribution of data over the architecture directly influences the efficiency of the simulation.
In addition, so as to improve the computational efficiency of the simulation tool, two optimizations are proposed.
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