AscendOptimizer: Episodic Agent for Ascend NPU Operator Optimization

## 论文概要 **研究领域**: ML **作者**: Jiehao Wu, Zixiao Huang, Wenhao Li, Chuyun Shen, Junjie Sheng, Xiangfeng Wang **发布时间**: 2026-03-26 **arXiv**: [2603.23566](https://arxiv.org/abs/2603.23566) ## 中文摘要 本研究探索了ML领域的前沿问题。研究团队来自Jiehao Wu, Zixiao Huang等。该方法在相关任务中展现了良好的性能和创新性。 原文摘要：AscendC operator optimization on Huawei Ascend neural processing units (NPUs) faces a two-fold knowledge bottleneck: unlike the CUDA ecosystem, there are few public reference implementations to learn from, and performance hinges on a coupled two-part artifact. We present AscendOptimizer, an episodic... ## 原文摘要 AscendC operator optimization on Huawei Ascend neural processing units (NPUs) faces a two-fold knowledge bottleneck: unlike the CUDA ecosystem, there are few public reference implementations to learn from, and performance hinges on a coupled two-part artifact. We present AscendOptimizer, an episodic agent that bootstraps this missing expertise by turning execution into experience. --- *自动采集于 2026-03-27* #论文 #arXiv #ML #小凯