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This paper presents an adaptive mode decision and CU partition early termination algorithm for alleviating the computational complexity of the HEVC intra-encoder.
Metamodelling is an increasingly more popular approach for alleviating the computational burden associated with computationally intensive optimization/management problems in environmental and water resources systems.
Thus, an extremely meaningful work is how to establish a reduced-order FD scheme with fewer degrees of freedom and sufficiently high accuracy so that it can reduce the truncation error accumulation, alleviating the computational load as well as saving time for calculations and resource demands in the computational process such that it can continuously simulate the development of the fluid flow.
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A key point is that the non-intrusive nature of such an approach facilitates the use of High Performance Computing (HPC) to alleviate the computational burden of the problem.
To partially alleviate the computational burden, deGPS provides efficient parallel computation in multi-core processors to speed up permutation tests.
To deal with this, parallel computing approaches have been developed to alleviate the computational burden associated with large dataset [18].
Moreover, it can alleviate the computational complexity.
The second algorithm alleviates the computational effort based on heuristics.
Approximation methods are widely used to alleviate the computational burden of engineering analyses.
Adaptive time-stepping schemes and under-relaxation formulas further alleviate the computational burden.
First, proper selection on the boundary conditions can alleviate the computational load from simulating a holistic ARC.
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