NVIDIA 详解 TensorRT 11.1 的 Global Performance Tuner 调优框架
NVIDIA 写了篇博客讲 TensorRT 11.1 的 Global Performance Tuner，教你理解为什么单个编译决策会拖垮端到端性能，做 PyTorch 推理优化的可以看看。
NVIDIA 发布博客，提出一套针对 PyTorch 模型性能优化的推理框架。文章解释了为什么单个编译决策看似有效却在端到端层面失效，以及精度如何约束性能优化。文中介绍了随 TensorRT 11.1 发布的 Global Performance Tuner，可自动完成性能调优，并配以直观示例和数学框架说明。
This blog post from @nvidia is intended to develop a clearer way of reasoning about performance optimization for PyTorch models and other representations.
It explores questions such as: What makes one compiled engine better than another? Why can individually promising decisions fail end to end? How should accuracy constrain performance optimization?
It introduces the Global Performance Tuner, a feature for automatic performance tuning released in TensorRT 11.1, and explores these questions through an intuitive example and a mathematical framework.
Read the full blog post here: https://t.co/KyfM4tzxaw
- kimmonismus15:27原文
