Scalable machine learning models for predicting quantum transport in disordered 2D hexagonal materials

· · 来源:tutorial资讯

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We benchmarked native WebStream pipeThrough at 630 MB/s for 1KB chunks. Node.js pipeline() with the same passthrough transform: ~7,900 MB/s. That is a 12x gap, and the difference is almost entirely Promise and object allocation overhead."

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