Revisiting phonon thermal transport in penta-graphene via a machine-learning potential-driven large-scale molecular dynamics simulation

· · 来源:tutorial资讯

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A. Preprocessing (Done by OsmAnd when new maps are prepared):

Create custom tuning profiles that take advantage of the inherent quantities of the input data and CPU thread saturation/scheduling/parallelization to optimize the crate such that ALL benchmarks run 60% or quicker (1.4x faster). You can use the flamegraph crate to help with the profiling

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edges: “soft contours”