vwf
play

VWF Automated Design of Experiments (DOE) and Optimization - PowerPoint PPT Presentation

Mar 15, 2023 •646 likes •1.35k views

VWF Automated Design of Experiments (DOE) and Optimization Framework Contents Introduction Benefit and Advantages Architecture Case study Conclusion - 2 - VWF Automated Design of Experiments (DOE) and Optimization

  1. VWF Automated Design of Experiments (DOE) and Optimization Framework

  2. Contents  Introduction  Benefit and Advantages  Architecture  Case study  Conclusion - 2 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  3. Introduction VWF is software used for performing Design of Experiments (DOE) and Optimization Experiments. Split-lots can be used in various pre-defined analysis methods. Optimization algorithms can be used for automated parameter variation. Scripts can be used to define custom DOE algorithms. Split parameters can be defined for any of Silvaco’s process, device, parasitic extraction and circuit simulators. All simulations can be carried out in parallel either on a cluster of workstations or on a single SMP machine. VWF comes with a GUI, that also enables examination of experimental results. - 3 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  4. Advantages  Integrates SILVACO’s simulators into one graphical user interface  Offers wide range of pre-defined DOE strategies (including: Full-Factorial, Half-Factorial and Box-Behnken)  Offers a JavaScript interface to implement own DOE strategies  Allows to import DOE definitions from a comma separated values (CSV) file  Offers many Optimization Algorithms (including: Levenberg-Marquardt, Genetic Algorithm, Parallel Tempering, Simulated annealing)  Offers a JavaScript interface for scripted optimization target computation  Supports Sensitivity Analysis: Study the effects of varying process input parameters on structural and electrical characteristics - 4 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  5. Advantages  Is Time and processor efficient – Supported computing environments range from single SMP workstations to large grid computing clusters (including Sun Grid Engine and LSF)  Supports both database (powerful SQL-92 compliant database) and file mode data storage environments  Increases productivity by ease of use and automation  Facilitates effective transfer of technology from development to manufacturing  Reduces cycle-time for development of new process technology  Allows central TCAD groups to generate results which are used by general engineering groups in a simple to use environment  Supports the Silvaco SRDB database concept to backup and restore databases easily - 5 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  6. Advantages  Supports multiple databases  Seamlessly invokes analysis tools (e.g. TonyPlot and SPAYN)  Allows Response Surface Model (RSM) generation  Effortlessly exports worksheet data results in common formats (e.g. CSV)  Offers powerful import and export capabilities to easily exchange data via zipped TAR files  Offers an Interface to the CVS version control system to import simulation decks  Supports a JavaScript batch mode to sequentially run experiments outside the main VWF application.  Comes with a comprehensive set of representative examples VWF – Automated Design of Experiments (DOE) and Optimization Framework

  7. VWF Architecture  Graphical User Interface (GUI) – Main application to define, control, run and analyze experiments  VWF Background Module – Runs experiments in the background when GUI is closed  VWF Database – Stores data like the simulation deck and split definitions, as well as simulation results  VWF File space – Holds all simulation result files like generated structures and runtime output  VWF Visualization Module – Offers powerful visualization and post- processing facilities  VWF Import/Export – Allows to move an experiment from one database to another  VWF Backup/Restore facility – Perform regular automated backups of data - 7 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  8. VWF Architecture: Database Access  Access multiple databases on several hosts through user name and password - 8 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  9. VWF Architecture: Secure Database Explorer  Protection of experiments by individual user permissions VWF – Automated Design of Experiments (DOE) and Optimization Framework

  10. VWF Architecture: Experiment Definition  Input decks can be loaded from text files, pasted from another directory, imported from deckbuild, or loaded from a CSV repository. - 10 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  11. VWF Architecture: Experiment Definition  Any parameter from any simulator can be defined graphically as a variable QUEST ATLAS SmartSpice - 11 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  12. VWF Architecture: Experiment Definition  External files used in the input deck are loaded in the database using the Resources menu External file - 12 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  13. VWF Architecture: Experiment Definition  Parameters can be varied in many ways, ranging from manual selection over pre-defined DOEs, to custom DOEs in JavaScript script, or one of many optimizer algorithms. - 13 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  14. VWF Architecture: Experiment Definition  Meaningful description of the experiment can be added within the Description Tab  Actions made on each experiment are recorded and can be retrieved in the Logging pane VWF – Automated Design of Experiments (DOE) and Optimization Framework

  15. VWF Architecture: Experiment Definition  Properties of the experiment can be comprehensively configured using the Setup Tab VWF – Automated Design of Experiments (DOE) and Optimization Framework

  16. VWF Architecture: Experiment Definition  Open Interface (Java Script) for implementing own DOE algorithms VWF – Automated Design of Experiments (DOE) and Optimization Framework

  17. VWF Architecture: Experiment Definition  Open Interface (Java Script) for implementing custom optimization target functions  Complex experiment types combining DOE and optimization VWF – Automated Design of Experiments (DOE) and Optimization Framework

  18. VWF Architecture: Experiment Execution  Sun Grid Engine (SGE) and LSF Compatible  Can utilize local multi processor machine - 18 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  19. VWF Architecture: Experiment Execution  The experiment and its status can be viewed as a Tree , a Worksheet or as Jobs - 19 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  20. VWF Architecture: Experiment Execution  Run-time output and simulation results are attached to each node and are available in real time  Can be retrieved from all views - 20 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  21. VWF Architecture: Experiment Execution  Summary of extracted data is available in real time within the Worksheet Tab - 21 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  22. VWF Architecture: Experiment Execution  View output of simulation results and JavaScript target function (cost) for combined DOE and optimization experiments Simulation results Target function (cost) VWF – Automated Design of Experiments (DOE) and Optimization Framework

  23. VWF Architecture: Experiment Analysis  Results can be analyzed directly in the Worksheet in text form or in graphical form ( TonyPlot interface ) - 23 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  24. VWF Architecture: Experiment Analysis  Efficiently select files for plotting in the SplitPlot Worksheet Tab Cell numbers (3.1, 3.3 and 3.6) are shown in the plot VWF – Automated Design of Experiments (DOE) and Optimization Framework

  25. VWF Architecture: Experiment Analysis  Convergence of the optimizer can be graphically visualized during an optimization experiment - 25 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  26. VWF Architecture: Experiment Analysis  A direct link to SPAYN allows statistical analysis and RSM generation for DOE experiments - 26 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  27. VWF Architecture: Experiment Analysis  RSM generation done in SPAYN can be visualized in TonyPlot - 27 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  28. Case Study  Sensitivity Analysis  Impact of Process Variation on Circuit Performance  3D Parasitic Capacitance Optimization  3D Stress Simulation for Mobility Enhancement Optimization  CIGS Solar Cell Optimization  Ge solar cell External Quantum Efficiency Optimization  Inductor Performance Optimization  Inductor PDK Generation  Comparison between Doe and Optimization approaches  Managing Circuit Simulation - 28 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

  29. Sensitivity Analysis  Sensitivity analysis in VWF allows quick and efficient parameter screening in order to reduce the number of variables to be used in a subsequent DOE - 29 - VWF – Automated Design of Experiments (DOE) and Optimization Framework

Recommend

More recommend