利用全球性能图纳扩展 NVIDIA TensorRT 单建路以外性能优化，第一部分

部署训练有素的神经网络不仅涉及将每个操作员翻译成GPU内核。 这是一个汇编问题，有许多合理的答案。 例如，当NVIDIA TensorRT构建一个引擎时，它会就图-IR的转换，聚变，执行选择，内存布置，和量子化做出相互依存的决定。 这个过程叫做排程。

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Deploying a trained neural network involves more than translating each operator into a GPU kernel. It is a compilation problem with many legitimate answers. For example, when NVIDIA TensorRT builds an engine, it makes interdependent decisions about graph-IR transformations, fusion, implementation selection, memory placement, and quantization. This process is called scheduling.

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