A Formal Model For Real-Time Parallel Computation Peter Hui SatishChikkagoudar PacificNorthwestNationalLaboratory Washington,USA peter.hui@pnnl.gov satish.chikkagoudar@pnnl.gov The imposition of real-time constraints on a parallel computing environment— specifically high- performance,cluster-computingsystems—introducesavarietyofchallengeswithrespecttothefor- malverificationofthesystem’stimingproperties.Inthispaper,webrieflymotivatetheneedforsuch asystem,andweintroduceanautomaton-basedmethodforperformingsuchformalverification.We definetheconceptofaconsistentparalleltimingsystem:ahybridsystemconsistingofasetoftimed automata(specifically,timedBu¨chiautomataaswellasatimedvariantofstandardfiniteautomata), intendedtomodelthetimingpropertiesofawell-behavedreal-timeparallelsystem. Finally,wegive a brief case study to demonstratethe conceptsin the paper: a parallelmatrixmultiplicationkernel which operates within provable upper time bounds. We give the algorithm used, a corresponding consistentparalleltimingsystem, andempiricalresultsshowingthatthe systemoperatesunderthe specifiedtimingconstraints. 1 Introduction Real-time computing has traditionally been considered largely in the context of single-processor and embedded systems, andindeed, thetermsreal-time computing, embedded systems, andcontrol systems areoften mentioned inclosely related contexts. However, real-time computing inthecontext ofmultin- ode systems, specifically high-performance, cluster-computing systems, remains relatively unexplored. Itcanbearguedthatonereasonfortherelativedearthofworkinthisareaisthelackofscenariostodate whichwouldrequire such asystem. Previously [11,12],wehavemotivated theemerging needforsuch aninfrastructure, givingaspecificscenariorelatedtothenextgenerationNorthAmericanelectricalgrid. Inthatwork,wedescribedthechangesandchallengesinthepowergriddrivingtheneedformuchhigher levelsofcomputational resourcesforpowergridoperations. Tobrieflysummarize(andtoprovidesome motivational context forthecurrent work), manyofthese computations— particularly floating-point in- tensive simulations and optimization calculations ([2, 3, 8, 9, 10])—can be more effectively done in a centralized manner, and the amount and scale of such data is estimated by some [11, 12] to be on the order of terabytes per day of streaming sensor data (e.g. Phasor Measurement Units (PMUs)), with the need to analyze thedata within astrict cyclical window (every 30ms), presumably with theaid ofhigh- performance, parallel computing infrastructures. With this in mind, the current work is part of a larger research effort at Pacific Northwest National Laboratory aimed at developing the necessary infrastruc- turetosupportanHPCclusterenvironmentcapableofprocessingvastamountsofstreamingsensordata underhardreal-timeconstraints. While verifying the timing properties of a more traditional (e.g. embedded) real-time system poses complex questions in its own right, imposing real-time constraints on a parallel (cluster) computing environmentintroducesanentirelynewsetofchallengesnotseeninthesemoretraditionalenvironments. Forexample,inadditiontostandardreal-timeconceptssuchasworst-caseexecutiontime(WCET),real- time parallel computation introduces the necessity of considering worst case transmission time when C.ArthoandP.C.O¨lveczky(Eds.):FTSCS2012 EPTCS105,2012,pp.39–55,doi:10.4204/EPTCS.105.4 40 FormalModelforRTParallelComputation communicating overthe network between nodes, aswell asthe need toensure that timing properties of oneprocess donotinvalidate thoseoftheentireparallelprocess asawhole. These are but two examples of the many questions which must be addressed in a real-time parallel computing system; certainly there aremanymore questions than can beaddressed inasingle paper. To this end, weintroduce asimple, event driven, automata-based model of computation intended tomodel the timing properties of a specific class of parallel programs. Namely, we consider SPMD(Single Pro- gram,MultipleData),parent-child typeprograms,inpartbecauseinpractice,manyparallelprograms— including many prototypical MPI-based [13, 15] programs— fall into this category. We give an example of such aprogram inSection 3. This model istypified by the existence of acyclic master or parent process,andasetofnoncyclicchildorslaveprocessesamongstwhichworkisdivided. Withthischarac- terization, averynatural correspondence emergesbetweentheprocesses andtheautomatawhichmodel them: thecyclicparentprocessisverynaturallymodeledbyanw -automaton,andthechildprocessesby astandard finiteautomaton. Ourmaincontribution ofthispaper, then,istwofold: first,aformalmethod ofmodelingtherespectiveprocesses inthismanner,combining theseintoasinglehybridsystemofpar- allel automata, and secondly, a simple case study demonstrating a practical application of this system. We should note that the notion of parallel finite automata is not a new one; variants have been studied before (e.g. [6,14]). Wetakethenovelapproach ofcombining timed variants ([1,5])offiniteautomata intoasinglehybridmodelwhichcapturesthetimingproperties ofthevariouscomponentprocesses ofa parallel system. The rest of the paper proceeds as follows: Section 2 defines the automaton models used by our system: Timed Finite Automata in Section 2.1, Timed Bu¨chi Automata in Section 2.2, and a hybrid system combining these two models in Section 2.3. Section 3 gives a case study in the form of an example real-time matrix multiplication kernel, running onasmall, four-node real-time parallel cluster. Section4concludes. 2 Formalisms Inthissection, wegiveformaldefinitionsforthemachineryusedinourhybridsystemofautomata. The definitions giveninSections2.1and2.2arenotnew[1]. However,itisstillimportantthatwestatetheir definitions here,astheyareusedlateron,inSection2.3. 2.1 Timed FiniteAutomata Inthissection,wedefineasimpletimedextensionoftraditional finitestateautomataandthewordsthey accept. Wewillusetheseinlatersectionstomodelthetimingpropertiesofchildprocessesinareal-time clustersystem. Timed strings take the form (s¯,t¯), where s¯ is a string of symbols, and t¯ is a monotonically in- creasing sequence ofreals (timestamps). t denotes the timestamp at whichsymbol s occurs. Wealso x x use the notation (s ,t ) to denote a particular symbol/timestamp pair. For instance, the timed string x x ((abc),(1,10,11)) is equivalent to the sequence (a,1)(b,10)(c,11), and both represent the case where ‘a’occursattime1,‘b’attime10,and‘c’attime11. Correspondingly, weextendtraditional finiteautomatatoincludeasetoftimers,whichimposetem- poral restrictions along state transitions. A timer can be initialized along a transition, setting its value to 0 when the transition is taken, and it can be used along atransition, indicating that the transition can onlybetakenifthevalueofthetimersatisfiesthespecifiedconstraint. Formally,weassociate witheach P.Hui&S.Chikkagoudar 41 automaton aset oftimer variables T¯, andfollowing the nomenclature of[1], aninterpretation n forthis setoftimersisanassignment ofarealvaluetoeachofthetimersinT¯. Wewriten [T 0]todenote the 7→ interpretation n with the value of timer Treset to 0. Clock constraints consist of conjunctions of upper bounds: Definition1. ForasetT¯ ofclockvariables, thesetX(T¯)ofclockconstraints c isdefinedinductively as c :=(T

A Formal Model For Real-Time Parallel Computation

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