---
格式版本: 2
标题: "Adaptive Matrix Multiplication for Dynamic Shapes on Ascend NPUs"
原文链接: "https://arxiv.org/abs/2608.10803"
发布日期: "2026-08-11"
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入库时间: "2026-08-12T03:03:08.976Z"
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AI优质: "否"
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去重键: "https://arxiv.org/abs/2608.10803"
---

## Computer Science > Hardware Architecture

## Title:Adaptive Matrix Multiplication for Dynamic Shapes on Ascend NPUs

[View PDF](https://arxiv.org/pdf/2608.10803) [HTML (experimental)](https://arxiv.org/html/2608.10803v1)

> Abstract:Matrix Multiplication (MatMul) faces a "generalization crisis" driven by highly dynamic tensor shapes. This crisis is particularly acute on Ascend NPUs, where explicitly controlled architectures and strict physical constraints render existing GPU-centric optimizations ineffective. To resolve this, we propose AdaptCore, an adaptive framework for universally high-performance MatMul on Ascend NPUs. AdaptCore systematically decouples operator optimization into spatial tiling and instruction orchestration. It first maps dynamic shapes into a hardware-aware 2D tiling taxonomy to balance on-chip capacity limits and multi-core parallelism. Furthermore, it integrates a composable optimization library with a deterministic analytical performance model. By mathematically evaluating hardware state mutations, AdaptCore proactively selects and caches optimal implementations, enabling O(1) overhead runtime dispatching. Evaluations demonstrate that AdaptCore delivers a remarkable 1.85x mean speedup across 80,000 input shapes, and achieves up to a 1.48x acceleration in representative end-to-end models over the highly-tuned native vendor library (ACLNN).

| Subjects: | Hardware Architecture (cs.AR) |
| --- | --- |
| Cite as: | [arXiv:2608.10803](https://arxiv.org/abs/2608.10803) \[cs.AR\] |
|  | (or [arXiv:2608.10803v1](https://arxiv.org/abs/2608.10803v1) \[cs.AR\] for this version) |
|  | [https://doi.org/10.48550/arXiv.2608.10803](https://doi.org/10.48550/arXiv.2608.10803) |

## Submission history

From: Yuhang Zhou \[[view email](https://arxiv.org/show-email/abd4312c/2608.10803)\]  
**\[v1\]** Tue, 11 Aug 2026 11:22:19 UTC (4,079 KB)

[Which authors of this paper are endorsers?](https://arxiv.org/auth/show-endorsers/2608.10803) | Disable MathJax ([What is MathJax?](https://info.arxiv.org/help/mathjax.html))
