DNA: A General D ynamic Neural N etwork A ccelerator
文献类型:期刊论文
| 作者 | Liu, Lian1,2; Yu, Jinxin1,2; Wang, Mengdi1,2; Li, Xiaowei1,2; Han, Yinhe1,2; Wang, Ying1,2 |
| 刊名 | IEEE TRANSACTIONS ON COMPUTERS
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| 出版日期 | 2025-09-01 |
| 卷号 | 74期号:9页码:3210-3222 |
| 关键词 | Dynamic scheduling Artificial neural networks DNA Processor scheduling Loading Prefetching Runtime Costs Switches Optimization Dynamic NN NPU design accelerator |
| ISSN号 | 0018-9340 |
| DOI | 10.1109/TC.2025.3587617 |
| 英文摘要 | Due to the demonstrated superiority, dynamic neural networks (NNs), which adapt their network structures to different inputs, have been recognized as an optimized alternative to conventional static NNs. However, researchers have not explored the implications of dynamic NN on neural processing unit (NPU) architecture design. Consequently, we analyze the characteristics and inefficient sources of executing dynamic NNs on existing hardware. From our analysis, existing NPUs, designed for static NNs, cannot effectively handle the execution of dynamic operator and agent-dependent data loading in dynamic NNs. To this end, we present DNA, an efficient accelerator optimized to deal with the challenges of running general dynamic NNs. Firstly, to improve the execution efficiency of dynamic operators, we propose a transverter-based online scheduling strategy to rapidly generate efficient scheduling for each dynamic operator. Secondly, to mitigate hardware idleness caused by the non-deterministic and agent-dependent data access patterns in dynamic NNs, we propose a novel predictor-based prefetching strategy that achieves effective data preloading with negligible cost. We implemented our accelerator, DNA, by integrating an additional online scheduler into a typical many-core baseline accelerator. According to our evaluation of various dynamic NNs, DNA achieves 3.48x speedup and 3.03 x energy savings over the baseline accelerator. |
| 资助项目 | National Natural Science Foundation of China[62025404] ; National Natural Science Foundation of China[62222411] ; National Key R&D Program of China[2023YFB4404400] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001561348800003 |
| 出版者 | IEEE COMPUTER SOC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/41710] ![]() |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Wang, Ying |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Dept Comp Sci, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 |
Liu, Lian,Yu, Jinxin,Wang, Mengdi,et al. DNA: A General |
| APA |
Liu, Lian,Yu, Jinxin,Wang, Mengdi,Li, Xiaowei,Han, Yinhe,&Wang, Ying.(2025).DNA: A General |
| MLA |
Liu, Lian,et al."DNA: A General |
入库方式: OAI收割
来源:计算技术研究所
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