Model-Implementation Fidelity in Cyber Physical System Design

244 Pages·2017·8.989 MB·English

by  Anca Molnos, Christian Fabre (eds.)

Anca Molnos · Christian Fabre Editors
Model-Implementation
Fidelity in Cyber
Physical System Design
Model-Implementation Fidelity in Cyber Physical
System Design
Anca Molnos • Christian Fabre
Editors
Model-Implementation
Fidelity in Cyber Physical
System Design
123
Editors
AncaMolnos ChristianFabre
CampusMINATEC CampusMINATEC
CEA,Grenoble,France CEA,Grenoble,France
ISBN978-3-319-47306-2 ISBN978-3-319-47307-9 (eBook)
DOI10.1007/978-3-319-47307-9
LibraryofCongressControlNumber:2016958303
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Preface
Thetrendtowardslarge-scaledeploymentsofcyber-physicalsystems(CPSs)makes
analysis of computing and physical world interactions of paramount importance.
Duringthedevelopmentofthesoftware,designersmodelthephysicalworldthatthe
futureCPSwillinteractwith.Someofthesemodelsrepresenttheexternalphysical
worldthattheCPSwillmonitorandcontrol,andothersrepresentaphysicalpartof
theCPSitself:itscomputingplatform,sensorsandactuators.
Modelsarebuiltwithvarioustechniquesandgranularity.Severalofthesemodels
areusedatvariousstagesoftheCPSlifecycle,fromtheearlystagesofspecification
todevelopmentandallthewaytoproductiontimewhenaCPSisactuallydeployed.
Furthermore,theyareinvolvednotonlyinthedevelopmentofthesoftwarebutalso
intheassessmentoffunctionalandnon-functionalpropertiesofthefullCPS.
As a consequence, CPS software development raises several questions on the
fidelityofmodels:
(cid:129) What is the fidelity of a model with regard to the part of the physical world it
represents?
(cid:129) To what extent is a model’s fidelity adequate, i.e. accurate enough but not too
complex or costly, with regard to the way the model will be used by the CPS
software?
(cid:129) What is the impact of a model’s fidelity on key properties of the full CPS, like
dependability,performanceorenergyconsumption?
These three questions lay beneath the authors’ contributions. The chapters
address several crucial CPS design aspects such as cross-application interference,
parsimonious modelling and trustful code production. The book describes a wide
range of solutions from simulation for extra-functional properties, extension of
programmingtechniques,model-drivendevelopment(MDD),resource-drivenmod-
elling and quantitative and qualitative verification based on statistics and formal
proofs.ThesesolutionsareappliedtoseveralCPSdesigntechniques:mixedcritical-
ity,communicationprotocolsandcomputingplatformsimulation.Tentativeanswers
are presented from very different communities, such as compiler construction,
v
vi Preface
power/temperature modelling of digital devices, high-level performance analysis,
code/devicecertification,etc.
ThetargetaudienceisresearchersandengineersinthefieldofCPSdevelopment
andvalidation.Theywillhavetheopportunitytolearnwhatisthecommonpractice
inthesefieldsand,moreimportantly,tomakethelinksbetweenthem.Trendsand
openresearchissuespresentedinthisbookcanbeaninspirationforfutureresearch.
Grenoble,France AncaMolnos
August29,2016 ChristianFabre
Introduction
ThisbookpresentsdifferentmodellingandanalysistechniquesusedforCPSdevel-
opment,suchasmodel-drivendevelopment(MDD),resource-drivendevelopment,
statisticalanalysisandproofsofsimulatorimplementation.Eachchapterdescribes
themodellingtechniquesusedandtheanalysisenabledtherebyanddiscussesmodel
fidelityinthisspecificcontext.
The first chapter overviews some of the sought challenges for building faithful
embeddedsystemsmodels,especiallythegrowingdemandforusingformalmodels
fordealingwith,e.g.,performance.Theimpactofthehardwarepartofthesystem
onperformanceisdiscussed,andaprobabilisticinterpretationisproposedtobuild
appropriately abstract models towards trustworthy analysis. Such a view is useful
to investigate the system performance as it provides a formal and parsimonious
framework.
The second chapter offers a view on how to manage the fidelity of a model’s
representation in order to control its complexity. This approach includes two
concrete and related methods targeting two aspects of the problem. Dynamic
resourcegraphshighlightthedependenciesbetweensystemresourcesanddescribe
a system’s progression as resource and dependency evolution steps. This forms a
theoreticalfoundationfortrackingtheparametersthatcanberegardedasresources,
e.g. power consumption, time and computation units. With this resource-oriented
view of a system, a hierarchical modelling method emphasising cross-layer cuts
isestablished.Thismethodfacilitatesparameter-proportionalmodellingtoachieve
fidelity vs. complexity trade-offs in models. Use-case simulation and state space
analysishelptovalidatetheapproach.
Thethirdchaptercoversthepower,thermalandreliabilityproblemsbroughtby
theextremedevice,coreandmulticorescalingthatwefacetoday.Asystemengineer
should be aware of any possible cross-application interferences with respect to
timing, power and thermal properties as soon as possible in the design process.
Power and temperature management should be dealt with without introducing
unwanted interference. For this reason, the extra-functional properties need to be
modelled and analysed at the system level, because they can strongly affect the
overallqualityofservice(QoS)—performanceandbatterylifetime—orevencause
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viii Introduction
the system to fail meeting its real-time and safety requirements. This covers the
specificationofplatformproperties(extra-functionalmodel)aswellasthedynamic
capturing, processing and extraction of power/temperature information during the
simulation.Especiallyclosingtheloopbacktotheapplicationandrun-timeservices
isanimportantfeatureforcomplexheterogeneoushardwareplatformsandsoftware
stacks.Asanexample,abattery-poweredmixed-criticalavionicssystem,runninga
safety-criticalflightcontrolapplicationandaperformancecriticalimageprocessing
applicationonthesamemulticoresystem-on-chip(SoC)ispresented.
Chapter4addressestheperformanceanalysisinrelationwiththeprogramming
models for the embedded domain. In particular, the focus is on synchronous
data flow (SDF) graphs that are often the computational model of choice for
specification, analysis and automated synthesis of parallel streaming kernels tar-
geting embedded multiprocessor system-on-chip (MPSoC) platforms. The chapter
discusses several limitations of the SDF graphs in the context of conventional
parallelsoftwaresynthesismethodologiesandhighlightstheassociateddegradation
of fidelity, in terms of analysis’ accuracy and synthesised software performance.
Subsequently, the chapter proposes several extensions to the strict notion of SDF
graph model that address the identified issues. An extensive empirical evaluation,
which underscores the model limitations and the effectiveness of the approach, is
included.
Chapter 5 presents a simulation view on the process of verification of MPSoC.
Thevirtualprototypingframework,SimSoC,isproposed.SimSoCisafullsystem
simulation framework based on SystemC and transaction-level modelling (TLM).
It takes as input a binary executable file, which can be a full operating system,
and simulates the behaviour of the target hardware on the host system. It is using
internally dynamic binary translation from target code to host code to simulate
the application software. A potential issue with simulators is that they might
not accurately simulate the real hardware. This gap is filled by proving that an
instructionsetsimulatorcodedinC(ofanARMprocessor,inourcase)isahigh-
fidelity implementation of the processor architecture. The first part of the chapter
presentsthegeneralarchitectureandfeaturesofSimSoC.Thesecondpartdescribes
theproofoftheARMsimulator.
Chapter 6 addresses the design and verification of mixed-critical systems from
modelsofcomputationtodescribeanapplicationallthewaytotheimplementation
on a hardware platform. The chapter describes a compositional method to design
applicationsindependentlyandthentoexecutethemwithoutinterference.Itdefines
aformalmodellingframeworkasasuitableentrypointforapplicationdesign.The
models are executable, which enables early detection of specification errors, and
include the formal properties of the applications based on well-defined models of
computation.ThisiscombinedwithapredictableMPSoCplatformtemplatethathas
asupportingdesignflow.Thestructureandbehaviouroftheapplicationmodelsare
exportedtoanintermediateformatviaintrospectionwhichisiterativelytransformed
forthebackendflow.Theproblemsarisinginthistransformationareidentifiedand
appropriate solutions are provided. The design flow is demonstrated by a system
consistingoftwostreamingapplications.
Introduction ix
Chapter 7 tackles the problem of qualitative and quantitative verification of an
embedded system via a holistic development approach. This includes visual mod-
ellingofthesystemanditsenvironment,qualitativeandquantitativeverificationof
themodelandautomatedexecutablecodegeneration.Anapplicationwithelectronic
tagsisutilisedtoillustratetheapproach.Tothisend,pState,atoolforthedesignand
verificationofhierarchicalstatemachines,isextendedwithprobabilistictransitions,
costs/rewardsandstateinvariants,calledpCharts.FromapChart,pStategenerates
inputcodeforaprobabilisticmodelcheckerintheformofeitheraMarkovdecision
process(MDP)oraprobabilistictimedautomaton(PTA).Onthegeneratedmodel,
qualitativeandquantitativepropertiescanbeverifiedtohelpassessitsfidelity.From
sub-chartswithoutprobabilistictransitions,pStatecangenerateexecutablecodein
Corassemblylanguage.
Finally, Chap.8 focusses on reducing the design gap between design complex-
ity and design productivity associated with the drastic increase of functionality,
implementedassoftwareordedicatedhardware,inembeddedMPSoCs.Thetrend
is to increase the level of abstraction at which designers and CAD tools work.
To deal with this problem, starting the design process from high-level UML
models combined with functional code using (i.e. in C/C++) the different system
components is presented. Video processing is one of the areas where high-level
modelling and analysis based on UML may have a wider impact. In this chapter,
MDDusingUML/MARTEisproposedtosupportthespecificationandanalysisof
apositioningsystemfor“recreatedreality”applications.
Thechaptersdescribetechniquesandgoalscharacteristicforseveralengineering
contexts: modelling of computing and communication, proof architecture models
andstatisticallybasedvalidationtechniques.
Contents
Introduction ...................................................................... vii
1 BuildingFaithfulEmbeddedSystemsModels:Challenges
andOpportunities............................................................ 1
AyoubNouri,MariusBozga,andSaddekBensalem
2 Resource-DrivenModellingforManagingModelFidelity.............. 25
Ashur Rafiev, Andrey Mokhov, Fei Xia, Alexei Iliasov,
Rem Gensh, Ali Aalsaud, Alexander Romanovsky,
andAlexYakovlev
3 EmpoweringMixed-CriticalitySystemEngineersinthe
Dark Silicon Era: Towards Power and Temperature
AnalysisofHeterogeneousMPSoCsatSystemLevel.................... 57
KimGrüttner
4 Throughput-DrivenParallelEmbeddedSoftwareSynthesis
fromSynchronousDataflowModels:CaveatsandRemedies........... 91
Matin Hashemi, Kamyar Mirzazad Barijough,
andSoheilGhiasi
5 SimSoC: A Fast, Proven Faithful, Full System Virtual
PrototypingFramework..................................................... 129
VaniaJoloboff,Jean-FrançoisMonin,andXiaomuShi
6 AComposableandPredictableMPSoCDesignFlowfor
MultipleReal-TimeApplications........................................... 157
Seyed-Hosein Attarzadeh-Niaki, Ekrem Altinel,
Martijn Koedam, Anca Molnos, Ingo Sander,
andKeesGoossens
7 Analysis and Implementation of Embedded System
Models:ExampleofTagsinItemManagementApplication............ 175
BojanNokovicandEmilSekerinski
xi