Inter-layer Scheduling Space Definition and Exploration for Tiled Accelerators
Jingwei Cai, Yuchen Wei, Zuotong Wu, Sen Peng, Kaisheng Ma
Abstract
With the continuous expansion of the DNN accelerator scale, inter-layer scheduling, which studies the allocation of computing resources to each layer and the computing order of all layers in a DNN, plays an increasingly important role in maintaining a high utilization rate and energy efficiency of DNN inference accelerators. However, current inter-layer scheduling is mainly conducted based on some heuristic patterns. The space of inter-layer scheduling has not been clearly defined, resulting in significantly limited optimization opportunities and a lack of understanding on different inter-layer scheduling choices and their consequences.
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Cited by top-tier papers13
- Gemini: Mapping and Architecture Co-exploration for Large-scale DNN Chiplet AcceleratorsJingwei Cai, Zuotong Wu, Sen Peng, Yuchen Wei et al.HPCA 2024 · 65 citations
- TileFlow: A Framework for Modeling Fusion Dataflow via Tree-based AnalysisSize Zheng, Siyuan Chen, Siyuan Gao, Liancheng Jia et al.MICRO 2023 · 31 citations
- MAGIS: Memory Optimization via Coordinated Graph Transformation and Scheduling for DNNRenze Chen, Zijian Ding, Size Zheng, Chengrui Zhang et al.ASPLOS 2024 · 14 citations
- SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module AcceleratorsMohanad Odema, Luke Chen, Hyoukjun Kwon, Mohammad Abdullah Al FaruqueMICRO 2024 · 11 citations
- Reconfigurable Stream Network ArchitectureChengyue Wang, Xiaofan Zhang, Jason Cong, James C. HoeISCA 2025 · 8 citations
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