Local linear instabilities in entropy-stable discretizations cause negligible practical errors because their growth is small, oscillatory, boundary-localized, and suppressible, with no direct extension to nonlinear two-point-flux cases.
Journal of Computational Physics382, 1–26 (2019)
2 Pith papers cite this work. Polarity classification is still indexing.
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GPU port of entropy-stable DG Euler solver with non-conservative buoyancy terms reaches nearly 70% of 64-bit peak on A100 volume kernels, delivers 10x speedup and 13x better energy efficiency versus CPU, and preserves symmetry-based flux savings.
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On the Practical Impact of Local Linear Instabilities in Entropy-Stable Schemes
Local linear instabilities in entropy-stable discretizations cause negligible practical errors because their growth is small, oscillatory, boundary-localized, and suppressible, with no direct extension to nonlinear two-point-flux cases.
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GPU Performance of an Entropy-Stable Discontinuous Galerkin Euler Solver with Non-Conservative Terms
GPU port of entropy-stable DG Euler solver with non-conservative buoyancy terms reaches nearly 70% of 64-bit peak on A100 volume kernels, delivers 10x speedup and 13x better energy efficiency versus CPU, and preserves symmetry-based flux savings.