EMS: efficient memory subsystem synthesis for spatial accelerators
Liancheng Jia, Yuyue Wang, Jingwen Leng, Yun Liang
2022Year
16Citations
2Top-tier citations
Abstract
Spatial accelerators provide massive parallelism with an array of homogeneous PEs, and enable efficient data reuse with PE array dataflow and on-chip memory. Many previous works have studied the dataflow architecture of spatial accelerators, including performance analysis and automatic generation. However, existing accelerator generators fail to exploit the entire memory-level reuse opportunities, and generate suboptimal designs with data duplication and inefficient interconnection.
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Install the CLIlune papers get 3a19e094-b98e-4702-a545-06cd65bdab29Cited by top-tier papers2
- Rubick: A Synthesis Framework for Spatial Architectures via Dataflow DecompositionZizhang Luo, Liqiang Lu, Size Zheng, Jieming Yin et al.DAC 2023 · 7 citations
- LEGO: Spatial Accelerator Generation and Optimization for Tensor ApplicationsYujun Lin, Zhekai Zhang, Song HanHPCA 2025
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