TileFlow: A Framework for Modeling Fusion Dataflow via Tree-based Analysis
Size Zheng, Siyuan Chen, Siyuan Gao, Liancheng Jia, Guangyu Sun, Runsheng Wang, Yun Liang · 2023
With the increasing size of DNN models and the growing discrepancy between compute performance and memory bandwidth, fusing multiple layers together to reduce off-chip memory access has become a popular approach in dataflow design. However, designing such dataflows requires flexible and accurate performance models to facilitate evaluation, architecture analysis, and design space exploration. Unfortunately, current state-of-the-art performance models are limited to the dataflows of single operator acceleration, making them inapplicable to operator fusion dataflows.