AscendOptimizer: Episodic Agent for Ascend NPU Operator Optimization
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
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
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*
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