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
Abstract
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.
Topics & Concepts
DataflowComputer scienceComputer architectureBandwidth (computing)Tree (set theory)ArchitectureDesign space explorationDistributed computingOperator (biology)Computer engineeringEmbedded systemParallel computingComputer networkVisual artsArtChemistryMathematicsTranscription factorRepressorGeneMathematical analysisBiochemistryParallel Computing and Optimization TechniquesEmbedded Systems Design TechniquesAdvanced Data Storage Technologies