Research in Model-Based Product Development at PELAB in ... · • GTI, USA • ISID Dentsu ... (PIM) Compilation &Code Gen (PSM) System Simulation Software & Syst Product Feedback

Presentation at MODPROD'2014PELAB – Programming Environment Laboratory

Department of Computer and Information ScienceLinköping University

2014-02-04

Peter Fritzson

Research in Model-Based Product Developmentat PELAB in the MODPROD Center

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2 © Peter Fritzson

Examples of Complex Systems in Engineering• Robotics• Automotive• Aircraft• Mobile Phone Systems• Business Software • Power plants• Heavy Vehicles• Process industry

3 © Peter Fritzson

Product models

Requirementsmodels

Unified Modeling: Meta-modeling& Modelica& UML & OWL

BusinessProcessControl

RequirementsCapture

Model-Driven Design(PIM)

Compilation & Code Gen

(PSM)

SystemSimulation

Software &Syst Product

Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels

Unified Modeling: Meta-modeling&Modelica& UML


RequirementsCapture

Model-Driven Design

Compilation& Code Gen

SystemSimulation

Software &System Product

Platformmodels

Processmodels

Open Standards – Modelica (HW, SW) and UML (SW)

Architecture of IntegratedModel-Based Product Development

4 © Peter Fritzson

Open Source Modelica Consortium

Open Source Effort

5 © Peter Fritzson

• Advanced Interactive Modelica compiler (OMC)• Supports most of the Modelica Language

• Basic environment for creating models• OMShell – an interactive command handler • OMNotebook – a literate programming notebook • MDT – an advanced textual environment in Eclipse

5

• OMEdit graphic Editor• OMOptim optimization subsyst• ModelicaML UML Profile• MetaModelica extension• ParModelica extension• OMPython – Python scripting

The OpenModelica Open Source Enviroment www.openmodelica.org

6 © Peter Fritzson

Industrial members• Bosch Rexroth AG, Germany •Siemens PLM, California, USA•Siemens Turbo, Sweden • CDAC Centre, Kerala, India • Creative Connections, Prague• DHI, Aarhus, Denmark• EDF, Paris, France• Equa Simulation AB, Sweden• Fraunhofer IWES, Bremerhaven• Fraunhofer FIRST, Berlin• Frontway AB, Sweden • IFP, Paris, France

Open-source community services• Website and Support Forum• Version-controlled source base• Bug database• Development courses• www.openmodelica.org

Code Statistics• Linköping University, Sweden• UC Berkeley, USA •TU Berlin, Insti UEBB, Germany• FH Bielefeld, Bielefeld, Germany•TU Braunschweig, Germany • Univ Calabria, Italy• Danish Technical Univ, Denmark•TU Dortmund, Germany•TU Dresden, Germany• Université Laval, Canada • Georgia InstiTechnology, USA• Ghent University, Belgium

University members

OSMC – International Consortium for Open Source Model-based Development Tools, 45 members Dec 2013

Founded Dec 4, 2007• GTI, USA• ISID Dentsu, Tokyo, Japan• ITI, Dresden, Germany• Maplesoft, Canada • Rickardo Inc., USA• STEAG, Dehli, India•TLK Thermo, Germany •Sozhou Tongyuan, China• VTI, Linköping, Sweden• VTT, Finland • Wolfram MathCore, Sweden

• Halmstad University, Sweden• Heidelberg University, Germany •TU Hamburg/Harburg Germany • KTH, Stockholm, Sweden • Univ of Maryland, Syst Eng USA • Univ of Maryland, CEEE, USA • Politecnico di Milano, Italy • Ecoles des Mines, CEP, France• Mälardalen University, Sweden • Univ Pisa, Italy•Telemark Univ College, Norway• Univ Ålesund, Norway

7 © Peter Fritzson

OpenModelica Environment Demo

8 © Peter Fritzson

General Tool Interoperability & Model ExchangeFunctional Mock-up Interface (FMI) The FMI development is result of the MODELISAR 29-partner project• FMI development initiated by Daimler• Improved Software/Model/Hardware-in-the-Loop Simulation, of physical

models and of AUTOSAR controller models from different vendors for automotive applications with different levels of detail.

• Open Standard• 14 automotive use cases for evaluation• > 30 tool vendors are supporting it

Enginewith ECU

Gearboxwith ECU

Thermalsystems

Automatedcargo door

Chassis components,roadway, ECU (e.g. ESP)

etc.

functional mockup interface for model exchange and tool couplingcourtesy Daimler

9 © Peter Fritzson

Research

Modeling-Language Design

Model-based Optimization

Fault Analysis – Bayesian Networks

Debugging

Multi-Core based Simulation

Modeling Support Environments

10 © Peter Fritzson

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels

Unified Modeling: Meta-modeling&Modelica& UML


RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels

OPENPROD – Large 28-partner European Project, 2009-2012 Vision of Cyber-Physical Model-Based Product Development

OPENPROD Vision of unified modeling framework for model-based product development.

Open Standards – Modelica (HW, SW) and UML (SW)


OPENPROD Model-Based Development EnvironmentCovers Product-Design V

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels

Unified Modeling: Meta-modeling& Modelica& UML


RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels

Specification

Design

DesignRefinement

Component verification

Subsystem level integration andverification

Subsystem level integration testcalibration and verification

Product verification anddeployment

Maintenance

Realization

Detailed feature design andimplementation

Architectural design and system functional design

Preliminary feature design

Systemrequirements

Level of Abstraction

Documentation, Version and Configuration Management

Verification

Integration

Calibration

Experience Feedback


Business Process Control and Modeling

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels



RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels

Metso Business model & simulationVTT Simantics Graphic Modeling Tool

OpenModelica based simulation

Simulation of 3 strategies with outcomes

VTT SimanticsBusiness process modeler

OpenModelicacompiler & simulator


Requirement Capture

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels



RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels

OpenModelica based simulation

vVDR (virtual Verification of Designs against Requirements)

in ModelicaML UML/Modelica Profile, part of OpenModelica

Design Model

Scenario Model

Requirement Models

Verification Model

Binding

Provider from design model

Client from requirement model


Model-Driven Whole-Product DesignSW/HW – UML/Modelica

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels



RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels

• SW modeled in UML: statecharts, activity diagrams

• UML translated to Modelica allows integration with Modelica (HW) models

Integrated SW/HW Modeling with ModelicaML/OpenModelica


Model-Driven Design, mostly with Modelica

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels



RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels

Sensitivity analysis(Appedge, IFPEN)

Acausal analysis for design(INSA, PSA)

Uncertainties modeling(EDF, LiU, MaCo)

Model Debugger(LiU)

Improved Type System(LMS, LiU)

Modeling & Design Tools

New Capabilities

Wolfram System Modeler(MaCo)

IDA Simulation(Equa)

Jmodelica.org, Optimica Studio)(Modelon)

BEAST(SKF)

Simantics(VTT)

Amesim(LMS)

BoGie(INSA)

AppEdge Sensi(Appedge)

TeamCenter(Siemens)

D&C System Simulator(Bosch-Rexroth)

Model Guidelines Checker(TUC, LiU)

Model Simplifier(Bosch-Rexroth)

OpenModelica(LIU, UBiele, MaCo, et al)


Compilation and Code Generation

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels



RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels

OMC QSS Codegen(ETH, LIU)

IDA Simulation(Equa)

Amesim(LMS)

OpenModelica Compiler (OMC)(LIU, UBiele, MaCo, et al)


OMC Inline Codegen(LiU, Ubiele)

OMC Parallel Codegen(LiU)

OMC Sparse Jacobians(UBiele)

DSP Codegen(LiU, MaCo)

Real-Time CodeGen SynDEx(IFP, INRIA)

OMC Symbolic Linearization(Ubiele, MaCo)

Model Compiling ToolsNew Capabilities

Simulation Efficient Storage(Maco, BR)

Multi-Rate Controller(Equa)

Real-Time Code Transform(CEA, LMS)


System Simulation

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels



RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels

Plexsim Simulator(Plexsim)

BEAST Simulator(SKF)

Wolfram Syst Modeler/Simulator(MaCo)

OpenModelica Simulator(LIU, Ubiele, MaCo, et al)

BEAST Parallel Solver(SKF, LIU)

Sparse-Matrix DAE Solver(XRG, BR)

OMC QSS Solver(ETH, LIU)

Plexsim QSS Solver(ETH, Plexsim)

OMC Interactive Simulation(EADS, LIU)

xMOD Simulator(IFP)

OMC Parallel Solver(LiU)

Simulation ToolsNew Capabilities

Solver Selection(LiU, MaCo)

OMC Modular Solver Runtime(BR, LiU)

Data Reconciliation(EDF, LIU, MaCo)

3D Graphic Animation(Fhg)


Interoperability

Product models

Requirementsmodels



RequirementsCapture



(PSM)

SystemSimulation


Feedback

Platformmodels

Processmodels

Product models

Requirementsmodels



RequirementsCapture

Model-Driven Design


SystemSimulation


Platformmodels

Processmodels


OpenModelica(LIU, Ubiele, MaCo, et al)

FMI 1.0 Prototypes(LiU, Modelon, MaCo, TLK, TUC)

XML Generation(Modelon, LIU)

xMOD(IFP)

TISC Co-Simulator for xIL(TLK)

Real-Time Co-Sim Platform(IFP, TLK, TUC)

OPC Data Access Server(VTT) Jmodelica.org, Optimica Studio

(Modelon)

FMI 2.0 Subset Co-simulator(LiU)

FMI 2.0 Sparse Jacobians(Ubiele, Modelon)

Flat Modelica export/import(LIU, Equa)

M&S Tools, PLM Tools

New Capabilities

TeamCenter(Siemens)

PDM System Integration(Siemens)


Modeling Language and Tool Research

• How can a modeling language be designedwith precise semantics to avoid errors?

• Can the language be made extensible?

• Can it model itself (meta-modeling)?

• How should a user-supportive modeling environment be designed?


Efficient Traceable Model-Based Dynamic Optimization – EDOp Research Project

Integrated modeling & optimization in OpenModelica Equation oriented tool, generation of efficient parallel code Based on OpenModelica, cooperation with Open-Source Consortium Including model error traceability and localization

Efficient solution methods for model-based optimization problems Methods can exploit structure of the problem and their equations Exploit models for parallel computing Utilize equations to analytically compute gradients and hessians, faster search

routines

Optimized Heavy Industrial Applications Trucks (Scania), Wheel Loaders (Volvo CE) Bearing applications in mechanical systems (e.g. wind power, SKF) Siemens: Gas turbines, Frontway: Process industry


OpenModelica Parallel Multiple-Shooting and Collocation Dynamic Trajectory Optimization

• Minimize a goal function subject to model equation constraints, useful e.g. for NMPC

• Multiple Shooting/Collocation• Solve sub-problem in each sub-interval

0,02,04,06,08,0

10,012,014,016,0

1 2 4 8 16

MULTIPLE_COLLOCATION

ipopt [scaled] jac_g [scaled]

Example speedup, 16 cores:

In OpenModelica Release1.9.1, non-parallel version.


OpenModelica Optimization SubsystemOMOptim• Parameter

optimization• Currently using

genetic optimization algorithms in OMOptim 0.9.

• Work on more parameter optimization

• Work on dynamic optimization using multi-corecomputers


Bayesian Network Based Fault and Failure Analysis – Cooperation with Scania, Mattias Nyberg

• Developing a Fault and Failure analysis tool for the engineers, containing the following features:

• Modelica/UML/SysML-like intuitive GUI design interface with simulation

• Functionality• Generate Failure Mode and Effect Analysis, FMEA table• Generate Fault Tree, FTA table• Answer to Queries• Probability of hazards• Root cause of hazards• Infer hazards, given the root cause


Legend

Bayesian Network Based Fault and Failure AnalysisAssociation of Services to the Components


Need for Debugging ToolsProblems and Motivation

• A major part of the total cost of software projects is due to testing and debugging

• US-Study 2002: Software errors cost the US economy annually~ 60 Billion $

• Large Gap in Abstraction Levelfrom Equations to Executable Code

• Example error message (hard to understand)Error solving nonlinear system 132

time = 0.002residual[0] = 0.288956x[0] = 1.105149residual[1] = 17.000400x[1] = 1.248448...


Algorithm Debugger in Eclipse OpenModelicaMDT Environment, Now also in OMEdit

• Eclipse plugin MDT (Modelica Development Tooling) is the integrated development environment

• Debugger is a debug plug-in within MDT

• Now also in OMEdit


Breakpoint Support in the Debugger

27


Equation Model Transformation Debugger

• Complicated to understand source of some errors• Trace transformations through the compiler

0 = y + der(x * time * z); z = 1.0;

(1) subst:

y + der(x * (time * z))

=>

y + der(x * (time * 1.0))

(2) simplify:

y + der(x * (time * 1.0))

=>

y + der(x * time)

(3) expand derivative (symbolic diff):

y + der(x * time)

=>

y + (x + der(x) * time)

(4) solve:

0.0 = y + (x + der(x) * time)

=>

der(x) = ((-y) - x) / timetime <> 0


Run-Time Debugger for Equation-Based ModelsIntegrated with OMEdit – first in any Modelica tool

Mapping error Positions backto source model

Tracing symbolictransformations


Run-Time Debugger for Equation-Based Models (2)


Integrated Hardware-Software Modeling

ModelicaML UML Profile for Modelica

SysML-Modelica Integration


Using ECLIPSE as Integration Platform

Java runtime

ECLIPSE Rich Client Platform (RCP) Runtime

ECLIPSE Process Framework (EPF) Composer Specific components

OpenModelica runtime

MetaModelica runtime

C/C++ runtime

ECLIPSE Modeling Framework

OpenModelicaMDT

Graphical Modeling Framework

UML-ModelicaPlug-in

OpenUP/Basic Capacity Sub-Process Areas


ModelicaML – UML Profile for Modelica1st Generation (2006-2008)

• Extension of SysML subset• Features:

• Supports Modelica constructs• Modelica generic class modeling• Modelica syntax in definitions• Equation-based modeling• Simulation modeling


ModelicaML UML Profile, 2nd Generation (2009-now)Also SysML/UML to Modelica OMG Standardization(with Wladimir Schamai, from 2009 until Now)

• ModelicaML is a UML Profile for SW/HW modeling• Applicable to “pure” UML or to other UML profiles, e.g. SysML

• Standardized Mapping UML/SysML to Modelica• Defines transformation/mapping for executable models• Being standardized by OMG

• ModelicaML• Defines graphical concrete syntax (graphical notation for diagram) for

representing Modelica constructs integrated with UML• Includes graphical formalisms (e.g. State Machines, Activities,

Requirements) • Which do not exist in Modelica language • Which are translated into executable Modelica code

• Is defined towards generation of executable Modelica code• Current implementation based on the Papyrus UML tool +

OpenModelica


ModelicaML: Graphical Notation

Structure

Behavior

Requirements


Example: Representation of System Structure

Interconnections

Inheritance

Components


Example: Representation of System Behavior

State Machine of

the Tank

State Machine of the

Controller

Conditional Algorithm

(Activity Diagram)


Example: Representation of System Requirements

Textual Requirement Formalized Requirement


Example: Simulation and Requirements Evaluation

Req. 001 is instantiated 2 times (there are 2 tanks in

the system)

tank-height is 0.6m

Req. 001 for the tank2 is violated

Req. 001 for the tank1 is not violated


System Tester

System Designer

Requirements Analyst

- 1. Select requirements to be verified using simulations (or logic tools)- 2. Formalize textual requirements

- Support Requirements Analyst in selecting requirements - 3. Create system design models to be verified against requirements- Support System Tester in deciding which requirements are to be

verified using which test cases- Support System Tester in linking requirement properties to design

model properties

- 4. Create test modes including test cases and decide which requirement are to be verified using which test cases

- 5. Link requirements to design models - 6. Simulate and observe requirement violations- 7. Analyze simulation results and create a Simulation Summary Report

vVDR – virtual Verification of Design Requirements vVDR Roles and Tasks (Wladimir Schamai PhD thesis Nov 2013)


Modeling Requirements in Modelica

• We need a way of marking requirements in models• introduce a new kind of specialized class: requirement• Requirement language constructs only valid within this kind of class

• 3-valued status of a requirement:• violated, not_violated, not_applicable

// Example Form-L: during (On and (MPSVoltage > V170)) check no (Off becomes true); requirement Req1b_is_on; input Real MPSVoltage;input Boolean on;input Boolean off;equationstatus = if (on and (MPSVoltage > V170)) then

if (off) then Status.violated else Status.not_violatedelse Status.not_applicable;

end Req1bis;


Automating Verification of Scenairo Model Composition using Bindings in Modelica

• Some models require data: Clients• Some models can provide require data: Providers• Clients and providers do not know each other a priori !

• Mediators relate a number of clients to a number of providers

MC

C

…

P

P

…

clients mediator providers


Parallel Execution Compilation to MultiCore


Towards High-Level Parallel Modeling and Simulation• Simulations are

time-consuming• Moore’s ”Law”: (since 1965)

• #devices per chip area doublesevery 18 months

• CPU clock rate also doubled every18 months – until 2003,

then: heat and power issues, limited ILP, ... superscalar technology has reached

its limits,only (thread-level) parallelism can increasethroughput substantially

• The consequence: Chip multiprocessors (+ clusters)• Multi-core, PIM, ... (for general-purpose computing)

• Need parallel programming/modeling/parallelization• Automatic parallelization• Explicit parallel modeling and parallel programming

Single-processor Performance Scaling

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

1984198619881990199219941996199820002002200420062008201020122014201620182020

Log

2 S

pee

du

p

Limit: Clock rate

Limit: RISC ILP

Throughput incr. 55%/year

65 nm45 nm 32nm 22nm90 nm

Pipelining

RISC/CISC CPI

Device speed

Parallelism

Assumed increase17%/year possible

Source: Doug Burger, UT Austin 20052006


Integrating Parallelism and Mathematical ModelsThree Approaches

• Automatic Parallelization of Mathematical Models (ModPar)• Parallelism over the numeric solver method.• Parallelism over time. • Parallelism over the model equation system

• ... with fine-grained task scheduling

• Coarse-Grained Explicit Parallelization Using Components• The programmer partitions the application into computational components

using strongly-typed communication interfaces. • Co-Simulation • Transmission-Line Modeling (TLM)

• Explicit Parallel Programming • Providing general, easy-to-use explicit parallel programming constructs

within the algorithmic part of the modeling language. • ParModelica, NestStepModelica


Modelica Simulations – Parallelization Approach

• Simulation = solution of (hybrid) DAEs from models

• In each step of numerical solver:• Calculate in g (and Y in h)

• Parallelization approach: perform the calculation of in parallel• Called parallelization over the system.

• Drawback: Numeric solver might become bottle-neck

00

),,(),,,(

tYXhtYXXg

X

X


Modelica + OpenCL = ParModelica

function parvarInteger m = 1024;Integer A[m];Integer B[m];parglobal Integer pm;parglobal Integer pn;parglobal Integer pA[m]; parglobal Integer pB[m];parlocal Integer ps;parlocal Integer pSS[10];

algorithmB := A;pA := A; //copy to deviceB := pA; //copy from devicepB := pA; //copy device to devicepm := m;n := pm;pn := pm;

end parvar;

ParModelica – Modelica Parallel Algorithmic ProgrammingHere: parglobal and parlocal Variables; Execution on GPUs

2014-47

Memory Regions

Accessible by

Global Memory All work-items in all work-groups

Constant Memory

All work-items in all work-groups

Local Memory All work-items in a work-group

Private Memory Priavte to a work-item


ParModelica Matrix Multiplication using Kernel function

Gained speedup• Intel Xeon E5520 CPU (16 cores) 26• NVIDIA Fermi-Tesla M2050 GPU (448 cores) 115

Speedup comparison to sequential algorithm on Intel Xeon E5520 CPU

32 64 128 256 512CPU E5520 (Serial) 0,093 0,741 5,875 58,426 465,234CPU E5520 (Parallel) 0,137 0,17 0,438 2,36 17,66GPU M2050 (Parallel) 1,215 1,217 1,274 1,625 4,057

0,06250,125

0,250,5

1248

163264

128256512

Sim

ulat

ion

Tim

e (s

econ

d)

4,36 13,4124,76 26,34

0,61 4,61

35,95

114,67

64 128 256 512Parameter M (Matrix sizes MxM)

SpeedupCPU E5520 GPU M2050

2014-48


New Scalable OpenModelica Parallel Code Generator

• Ongoing work• Both task parallelism and data parallelism• Handling non-expanded arrays efficiently• Includes use of TLM-partitioning for more parallelism

• OPENMP or Pthreads based parallelization prototype for equation-based models in OpenModelica

• ParModelica - Generating OpenCL code for platform independence

• Template based code generator


Summary of MODPROD Research at PELAB

• Modeling language design (semantics, type systems, meta-modeling, extensibility)

• Model-based efficient optimization (multi-core)• Fault estimation & traceability; Bayesian networks• Modelica-UMLSysML integration• Requirements traceability• Debugging of models• Compilation to multi-core platforms• Compilation and performance measurements for

real-time simulation

Documents

Research in Model-Based Product Development at PELAB in ... · • GTI, USA • ISID Dentsu ... (PIM) Compilation &Code Gen (PSM) System Simulation Software & Syst Product Feedback