计算机工程与应用2024，Vol.60Issue(17)：74-88,15.DOI:10.3778/j.issn.1002-8331.2311-0443
空间加速器的受约束数据流建模与评估框架
Modeling and Evaluation Framework for Constrained Dataflow in Spatial Accelerators
摘要
Abstract
Deploying tensor computation tasks on spatial accelerators has been proven to effectively improve the execu-tion speed and efficiency of tensor computations.To effectively deploy tensor computation on spatial accelerators,various dataflow modeling and evaluation frameworks have been proposed in academia.These frameworks enable quick evalua-tion of dataflows for efficient design space exploration.However,these frameworks lack fine-grained descriptions of the hardware structure,making it challenging to effectively model the constraints imposed by the hardware structure on the dataflow.As a result,they fail to explore the design space of dataflows constrained by real spatial accelerators effectively.To address this issue,this paper firstly provides a fine-grained modeling of the hardware architecture,using a multi-level spatial accelerator hardware structure as a template.Each level consists of three components:array structure,storage struc-ture,and interconnect network structure,to respectively describe the constraints of the hardware architecture on spatial unfolding of data flow,storage capacity,and data transmission methods.Then,this paper proposes a tensor computation task and dataflow modeling approach that can solve the resource requirements of the dataflow.Based on this,the paper further proposes a dataflow evaluation framework,consisting of three parts:requirement analysis,constraint analysis,and performance analysis.The requirement analysis is used to determine the demands of computation tasks and dataflows on hardware resources.The constraint analysis aims to examine whether the dataflow violates hardware structure constraints.The performance analysis is used to evaluate performance metrics such as latency,data reuse,and resource utilization of the dataflow.Experimental results demonstrate that compared to the state-of-the-art evaluation framework,the proposed framework reduces the error in latency evaluation,and effectively supports the exploration of constrained dataflow design space.关键词
张量计算/空间加速器/数据流/建模与评估/设计空间探索Key words
tensor computation/spatial accelerator/dataflow/modeling and evaluation/design space exploration分类
信息技术与安全科学引用本文复制引用
贺裕兴,王腾,滕文彬,宫磊..空间加速器的受约束数据流建模与评估框架[J].计算机工程与应用,2024,60(17):74-88,15.基金项目
国家重点研发计划(2022YFB4501600,2022YFB4501603) （2022YFB4501600,2022YFB4501603）
国家自然科学基金(62102383,61976200,62172380) （62102383,61976200,62172380）
江苏省自然科学基金(BK20210123) （BK20210123）
中国科学院青年创新促进会项目(Y2021121). （Y2021121）
