Role of Computer Experiment
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- Pauline Campbell
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1 Role of Computer Experiment Experimental World Computer Experiment Theoretical World Accumulation of factual information Checks and stimuli Ordering of factual information into logically coherent patterns to provide predictive laws Physical experiment Apparatus + data analysis Devices are expensive Data is inaccessible Phenomena are very complex Computer experiment Computer + program Complementing experiments/theory when Theory Mathematicl analysis + numerical evaluation Nonlinearity Many degree of freedom Lack of symmetry
2 A Word About Modeling Variables Physical phenomenon M o d e l Behavior Modeling Approximation (different levels) Simulation Trade-off (different considerations) A model of a physical device is a mathematical entity with precise laws relating its variables. The model is always distinct from the physical device, though its behavior ordinarily approximates that of the physical device represented. Thus a model is never strictly equivalent to the device it represents. John Linvill Everything should be made as simple as possible, but not any simpler. Albert Einstein
3 Driving the Simulation Vehicle Driver You User Defaults Meters Numerical physical models Engine Direction/target Roadmap Strategy Steering
4 Electronic Systems Input System electron Output Electronic System A black box which performs a certain function based on the laws of physics of the electrons Whenever you press the button of an electronic system, you are actually manipulating the motion of individual electrons.
5 Spectrum of Approaches to Analyzing Electronic System The Big Picture Physics Engineering Device Circuit System Quantum mechanical Monte Carlo Semiclassical Device Circuit Logic Driftdiffusion Hydrodynamic MC HD DD Electrical Behavioral Timing Switch Gate RTL Functional Structural Behavioral
6 VLSI Design and Manufacturing Hierarachy Behavioral System Structual Functional Technology independent Technology dependent Gate Circuit Switch Electrical Process independent SPICE Process dependent Drift-diffusion Device Hydrodynamic Front-end Monte Carlo Back-end Physical design Layout Tech file Physical fabrication Process A B C Parameter extraction Wafer Electrical measurement
7 VLSI Technology Development Device physics Technology Circuit design Device specification Process specification Mask specification Structure variation Scaling rule Process variation Design rule Mask variation Process flow Wafer
8 VLSI Process Development Fabrication/Measurement Simulation Process recipe Process specification Process models Wafer Process C V/SIMS measurement Electrical measurement Transient measurement Impurity profile Device characteristics Parameters for circuit Circuit performance Device Characterization Circuit Semiconductor physics models Circuit models
9 Three Ways of Obtaining Device Characteristics I V Experimental Numerical Analytical Wafer SMU, oscilloscope Partial differential equations + B.C. s 2D/3D grid, finiteelement MEDICI Closed-form equations Matrix, iteration SPICE What are the advantages of the numerical approach to device characterization?
10 TCAD Physical Simulation TCAD Layout + Process Process Device Technology characterization Circuit Goal: Emulate physical phenomena virtual wafer fabrication Semiconductor processing Device operation and electrical characterization Parasitic electrical effects Circuit performance
11 The Driving Force Deep Submicron Technology New device physics Pushing to the limit of conventional device modeling ( drift-diffusion ) Requiring advanced physical models and quantitative accuracy (3D) New technologies Pushing to the optical limit of conventional masking Requiring advanced processing technologies (E-beam, ) New design methodologies Interconnect parasitic plays a more critical role Multilayer technology complicates topography Maximum IC performance requires full-cell characterization
12 Role of TCAD in IC Engineering Software tools IC engineer groups Physical ECAD TCAD CIM Circuit design Technology development Manufacturing
13 Three Major Stages of Physical Simulation Stage Process Simulation Device Simulation Technology Characterization Motivation/Goal Process alternative evaluation Process sensitivity investigation Process centering and yield improvement Understanding physical effects Electrical characteristics prediction Device reliability study Device parameter extraction and optimization for circuit design Interconnect parasitic extraction for signal integrity analysis Full-cell extraction for technology development and library characterization
14 The Simulation Vehicle The simulator: The numerical engine of the vehicle. Back and front: What are the input and output parameters? Under the hood: What are the physical models? The key to effective use of a tool is to know what it is capable, and to use it as your tool, not your goal. Process Device Circuit
15 Process Simulation Input Ambient Process Steps Output Temperature Pressure Time Rate Dose Energy Thickness Diffusion Oxidation Ion implantation Deposition Etching Masking Epitaxy Structure Mesh Layer thickness Doping profile Junction depth Stress Device structure spec. Models & coefficients
16 Device Simulation Input Process Structure Mesh Doping User Grid Mesh Analytic profile Physical Models Recombination Bandgap/DOS Mobility Statistics Boundary Conditions Ohmic/Schottky Insulator/Neumann Interface charge/traps Lumped/distributed RC Numerical Methods Decoupled (Gummel) Coupled (Newton) Linear matrix Jacobian matrix Analyses Transient Small-signal AC Impact ionization Gate current Output Terminal characteristics I V, G V, C V 1D plots (along a line segment) Potential, field, band-edge, Fermilevel, doping, carrier temperture, carrier concentration, generation/ recombination rate, current density 2D plots Region boundaries, junctions, depletion regions, 3D plots (same quantities as 1D) Surface (projection of a 3D view) Vector (field, current density) Contour (same quantities as 1D)
17 Technology Characterization Input Device Parameter Models Output Measured or simulated electrical characteristics Input Lithography Topography GDS II Built-in: MOS/BSIM, BJT, JFET, Variables Voltage, geometry, temperature Currents Targets Optimization Data selection/weighting Interconnect Parasitic 2D/3D solver engine High-frequency analysis (including skin effect) SPICE model parameters Output SPICE equivalent RLC netlist Distributions: potential, current density, temperature RSM model from regression analysis: analytic models, rules for LPE 3D cell-level interconnect extraction
18 Circuit Simulation Input Matrix Solver Output Circuit netlist Control card LU decomposition Relaxation Event driven Selective trace Analyses Operating point/dc Small-signal AC Transient Elements Sources Linear/passive Nonlinear/active Subcircuits Device Models Diode BJT MOSFET JFET/MESFET Operating point I V characteristic Voltage/current transients Derived parameters Transconductance, Gain, Power, Delay,
19 Device vs Process Simulation Structure Mesh Impurity profile Device Simulation 2D/3D PDE Engine Drift diffusion Balance equation I V Process Simulation Boundary conditions Process models Recipe
20 Device vs Circuit Simulation Structure Mesh Impurity profile Boundary conditions Device Simulation Simulated I V I V Circuit Simulation Delay SPICE model parameter Measured I V
21 Role of Process and Device Simulation Process Stand-alone: simulate processing steps for evaluating process alternatives, sensitivity, and yield improvement Front-end to device simulator: provide realistic structure and impurity profile for meaningful device Device Stand-alone: simulate single-device electrical characteristics for understanding physical effects, advanced device design, and reliability study Front-end to circuit simulator: provide accurate parameters for transistorlevel models to predict circuit performance
22 Design of Experiment (DOE) Variables Model Targets Process Device Parameter extraction Circuit Circuit performance T, t V T I V I V T S P I C E E, Φ V t d
23 Response Surface Modeling (RSM) Coefficients RSM Data Min y(ξ 1,ξ 2, ξ N ) Response Diffusion Temperature Vt Channel Implant Dose
24 Virtual Device Fabrication V i r t u a l d e v i c e Structure editor & visualizer Layout Process Device Technology characterization Circuit Deposition/etch Photo-lithography 2D process sim 1D process sim LCD analysis 3D device sim Heterojunction device Lattice temperature Programmable device 2D device sim Optical device Trapped charge Anisotropic material Interconnect parasitic Circuit parameter Device-level circuit sim
25 TCAD Tools from Technology Modeling Associates TWB TMAVISUAL MICHELANGELO TMALAYOUT Process Device Technology characterization Circuit TERRAIN DEPICT TSUPREM-4 TSUPREM-3 LIQUID DAVINCI HD-AAM LT-AAM PD-AAM AM-AAM MEDICI TC-AAM OD-AAM RAPHAEL AURORA CA-AAM
26 Simulator Accuracy Relative accuracy of a simulator basic usage An inaccurate simulator can provide relatively accurate results in terms of the valuable insight into the different variable target dependencies Absolute accuracy of a simulator ultimate goal Accuracy of models ( physics) Accuracy of model coefficients ( calibration) Accuracy of s Accuracy of simulator + Proper use of simulator Essence of trade-off between accuracy and speed
27 General Tips on Using CAD Tools A simulator is only as good as the physics put into it Only what is well understood can be modeled Always with clear objectives for a Rely on your own judgement, not nor experimental results Be fully aware of the model assumptions and the default parameters Make sure the model is used in its region of validity Justify if defaults are to be used The result of a is grid dependent Trade-off between accuracy and speed Use coarse grids initially, refine the grids as you proceed Look for trends, not for accurate values Never try to perfectly fit a single set of parameters to an experimental curve Overall 10 20% accuracy would be a reasonably good fit
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