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上传人: 哆哆 编号:630974 2025-04-19 16页 1.67MB

1、Using AI to Improve EDA Tools for Multi-Die ArchitecturesChiplet SummitKamal Desai,Product ManagerSutirtha Kabir,Sr R&D Director1/22/25 2025 Synopsys,Inc.2Agenda AI Assisted,Early Architecture Exploration AI Enabled System Analysis&Optimization Flow 2025 Synopsys,Inc.3Power models and characterizati

2、onTypical Performance&Power Analysis FlowRoot-cause analysisSoftware andtracesmapApplication specificationApplication workloadWorkload trace and statisticsModel librariesHardware platformSensitivity analysisDesign space explorationand collaborationParameter SweepingManual StepsRequires expert design

3、 knowledge 2025 Synopsys,Inc.4Design Space Exploration,Time to Results ChallengesToo many scenarios for coverage of the entire design spaceNeed expert knowledge of parameter impact on KPIsManual,tedious tasks of identifying root causesRequires significant compute resources for entire design space 20

4、25 Synopsys,Inc.5Machine Learning for Design Space Exploration and Sensitivity Analysis Automatically setup all relevant scenarios and execute relevant ones only Nominal expert knowledge required on IP and design parameters Analysis results in fastest time while minimizing compute resources Expedite

5、d DesignRequirements with constraintsDesign with workloadExploration Space 2025 Synopsys,Inc.6AI Enabled Performance&Power Analysis FlowSimulate&AnalyzeRequirements Met?Executable Architecture Specification&Architecture Performance ReportYesNoRoot Cause Analysis +Structural ChangesStarts from requir

6、ements on KPIs,which guides the AI assisted explorationExploration space for the architecture needs to be Defined:which parameters should be modified?Constrained:which parameter values and which parameter value combinations are allowed?If there is a parameter configuration meeting all requirements T

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本文主要探讨了人工智能在改进多芯片架构的电子设计自动化(EDA)工具方面的应用。文中提到,借助AI,可以自动化设置和执行相关场景,从而在满足性能、功耗和面积要求的同时,显著缩短结果生成时间。AI辅助的设计探索和敏感性分析能够减少手动和繁琐的任务,以及所需的计算资源。例如,在AI的帮助下,从207,000个场景中,只需16个场景就满足了所有性能、功耗和面积的要求。此外,AI还能在设计空间探索和优化方面发挥作用,例如在3D结构的热/电压drop优化中,通过AI优化,顶部芯片的最大温度从108.6°C降低到101.3°C,最大电压降从52.8mV降低到27.4mV。总的来说,Synopsys的3DSO.ai平台通过AI技术优化了设计流程,提高了设计效率和质量。
"AI如何提升多芯片架构的EDA工具?" "3DIC编译器如何实现设计与性能的优化?" "Synopsys 3DSO.ai如何自动化专家级设计任务?"
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