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

· · 来源：hardware资讯

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GC thrashing in SSR: Batched chunks (Uint8Array[]) amortize async overhead. Sync pipelines via Stream.pullSync() eliminate promise allocation entirely for CPU-bound workloads.

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