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CODA: A Computation-Driven Paradigm for Sparse DNN Acceleration

文献类型：期刊论文

作者Liu, Yanhuan1,2; Li, Wenming1,2; Zhang, Kunming1,2; Liu, Tianyu1,2; Ye, Xiaochun1,2; An, Xuejun1,2
刊名IEEE COMPUTER ARCHITECTURE LETTERS
出版日期2025-07-01
卷号24期号:2页码:381-384
关键词Software Hardware Computational modeling Sparse matrices Pipelines Indexes Data models Spatial databases Computational efficiency Vectors Computation-driven architecture sparse DNN acceleration dataflow paradigm unstructured sparsity work tokenizer dynamic execution core asynchronous execution
ISSN号1556-6056
DOI10.1109/LCA.2025.3637756
英文摘要The spatial dataflow paradigm, while effective for dense workloads, collapses on unstructured sparsity, manifesting as a profound Twin Crisis: a high Latency Overhead (termed the Latency Crisis) driven by slow, dominant offline software preprocessing for data reordering and formatting, and an Inefficiency Crisis characterized by massive pipeline stalls that leave hardware underutilized. This paper introduces CODA, a novel computation-driven architecture that challenges this data-centric model by shifting the focus from "scheduling data" to "discovering work." CODA materializes this new paradigm through two core innovations. First, a hardware Work Tokenizer eliminates the preprocessing bottleneck on-the-fly, directly resolving the Latency Crisis. Second, a scalable Dynamic Execution Core performs asynchronous, pull-based dispatch of computable work packets to idle resources, which eradicates stalls and solves the Inefficiency Crisis. By directly resolving the Twin Crisis, CODA demonstrates superior performance over state-of-the-art accelerators like Mentor and Hirac. On the BERT-BASE benchmark, it achieves up to 3.95x higher speed, 3.4x greater energy efficiency, and a 3.1x reduction in end-to-end latency, establishing a necessary new architectural blueprint for sparse acceleration.
资助项目Beijing Natural Science Foundation[L234078]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001641467300003
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/42943]  
专题中国科学院计算技术研究所
通讯作者Li, Wenming
作者单位1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processors, Beijing 100045, Peoples R China
2.UCAS, Sch Comp Sci & Technol, Beijing 101408, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Yanhuan,Li, Wenming,Zhang, Kunming,et al. CODA: A Computation-Driven Paradigm for Sparse DNN Acceleration[J]. IEEE COMPUTER ARCHITECTURE LETTERS,2025,24(2):381-384.
APA Liu, Yanhuan,Li, Wenming,Zhang, Kunming,Liu, Tianyu,Ye, Xiaochun,&An, Xuejun.(2025).CODA: A Computation-Driven Paradigm for Sparse DNN Acceleration.IEEE COMPUTER ARCHITECTURE LETTERS,24(2),381-384.
MLA Liu, Yanhuan,et al."CODA: A Computation-Driven Paradigm for Sparse DNN Acceleration".IEEE COMPUTER ARCHITECTURE LETTERS 24.2(2025):381-384.

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来源：计算技术研究所

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