基于物理的机器学习和生成式 AI 用于科学和工业中的替代建模.pdf

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1、PHYSICS-INFORMED MACHINE LEARNING AND GENERATIVE AI FOR SURROGATE MODELING IN SCIENCE AND INDUSTRYMIKE OKEEFFE,SENIOR SOLUTIONS ARCHITECT,NVIDIANEW YORK SCIENTIFIC DATA SUMMIT 2024:ADDRESSING DATA CHALLENGES IN DIGITAL TWINSSCIENTIFIC COMPUTING IS EVOLVINGThought Leaders Map Out the Opportunity and

2、Constraints Given Current Technology and Market RealityBusiness-as-usual will not be adequate TRANSITION TO POST EXASCALE ERAFEATURETERA THROUGH EXASCALEPOST EXASCALEUSAGEBATCH&MOSTLY LOCAL TO A SITE INTERACTIVE&DISTRIBUTED WITH MULTIPLE SITESWORKLOAD SINGLE SIMULATION/ENSEMBLEWORKFLOW COMPRISED OF

3、SIMULATION ENSEMBLES,AI TRAINING AND INFERENCE,LIVE DATA ANALYTICSEXPERIMENTSOFFLINE DATA ANALYSIS FOR EXPERIMENTSMIX OF REAL-TIME ANALYSIS TIGHTLY COUPLED WITH OFFLINEDIGITAL TWINSIN-SITU VISUALIZATION OFFLNEINTERACTIVE VISUAL MODEL COUPLED WITH PHYSICAL ASSETQUANTUM COMPUTINGSIMULATIONSIMULATION P

4、REPARING FOR A HYBRID MODEL PROGRAMMING MODELSFORTRAN,C+,MPI,OPENMPSTANDARD PARALLELISM SUPPORT IN FORTRAN,C+,MPI,OPENMP,OPENACC,PYTHON,JULIA,PYTORCH,TENSORFLOWSYSTEM CONFIGURATIONMONOLITHICMODULARCLOUDGRIDBURST CAPABILITIES,FASTER REFRESH CYCLE,ACCESS TO LATEST TECHNOLOGY AT SCALEDIGITAL TWIN FOR S

5、CIENCEA Relatively New Modeling Concept That is Being Adopted by the HPC Community in the Post Moore EraThe concept was first publicly introduced in 2002 by Michael Grieves,at a Society of Manufacturing Engineers conference as the conceptual model underlying Product Life Cycle ManagementA digital tw

6、in is a set of virtual information constructs that mimics the structure,context,and behavior of a natural,engineered,or social system(or system-of-systems),is dynamically updated with data from its physical twin,has a predictive capability,and informs decisions that realize value.The bidirectional i