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Joshua Perez
Joshua Perez

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Various people have made efforts to use a different front end withPtolemy Classic. See thePtolemy Website Links Page for possible solutions,including: MLDesigner 2.1is a commercial product that was released in January 2002 and itincludes a conversion utility from Ptolemy Classic models. The PeaCE (Ptolemy extension as Codesign Environment)might offer some ideas and does have some software available.The 2001Ptolemy Miniconference had the following talk:"An Approach to Executing Ptolemy Classic Models under Ptolemy II"Ned Stoffel, Dwight Richards, Neil Smyth*, and Matt Goodman, TelcordiaTechnologies, Inc. (* Smyth is now with Altio).The slides for this talk can be found at We are not sure if Telcordia has any software available for release. 2.2 How are Ptolemy II and Matlab/Simulink different? Ptolemy II has very little in common with Matlab, which is a textual, imperative, interactive, scientific programming language. Ptolemy II works with Matlab, thanks to an interface developed by Zoltan Kemenczy and others at Research In Motion, Ltd. See Ptolemy II has much more in common with Simulink, which is a graphical block-diagram language, originally developed for control system design. Simulink has a rich and expressive model of computation with continuous-time semantics and support for periodic discrete-time signals. Some of its principles have been incorporated in the CT (continuous-time) domain of Ptolemy II, but not all. The CT domain, for example, does not have the notion of "sample time" (which in Simulink provides the periodic discrete-time support) nor the support for algebraic loops. There is also currently no code generation support in CT (in Simulink, this is provided through the associated product Real-Time Workshop). Also, the CT domain has implemented fewer ODE solvers than those provided by Simulink and has a smaller actor library. Ptolemy II and Simulink both support extension of the actor library through well-defined interfaces (in Simulink, this is called the S-function interface). However, Ptolemy II is a more open architecture in that its infrastructure is open source, and the interfaces to the core mechanisms in the software are published and documented. The persistent file format (MoML) is XML in Ptolemy II, which makes it both more verbose and more portable than the Simulink syntax (MDL files). Simulink supports one model of computation, whereas Ptolemy II supports several, and can be extended with new models of computation. Simulink can also be extended, as for example it has been with the associated product Stateflow, which supports state-machine modeling. But in Simulink, the extension is done by defining new blocks using the S-function interface. As such, additional models of computation added this way are second class. For example, they cannot define the model of computation at the top level of the hierarchy, and cannot contain Simulink models within their own components. 2.3 What is the relationship between Ptolemy and Metropolis? Ptolemy ( )and Metropolis ( ) are separate research projects at Berkeley,albeit ones with considerable cross-influences. Ptolemy is headed byEdward Lee,while Metropolis is headed by Alberto Sangiovanni-Vincentelli. A key principle in Metropolis is its "meta model," which in theterminology of the Ptolemy project we would call its "abstractsemantics." In Metropolis, models consist of processes, with their ownthread of control, that communicate through ports and "media." Themedia are roughly equivalent to Ptolemy Receivers; they define thecommunication semantics between components. The abstract semantics ofMetropolis, is an abstraction of the model of computation that appearsin the Ptolemy PN and CSP domains. It is an abstraction because inMetropolis, the communication semantics is not defined, whereas in PNand CSP, it is (in two different ways). Metropolis model buildersconstruct the media that processes use to communicate. One could build,for example, media in Metropolis to implement either PN or CSP.Moreover, Metropolis model builders construct much of what would be thedirector in a Ptolemy model. In Ptolemy, two parts of the abstract semantics are separated, controland communication. The abstract semantics of control is based on theExecutable interface. The abstract semantics of communication is basedon the IOPort/Receiver interface. The Metropolis metamodel is morefixed about control semantics (i.e. components are process based), butallows a richer interface to communications media (since a media canexpose arbitrary interfaces to components). This design choice makescommunication refinement easier (since the interface to a media canchange) but makes it more difficult to build domain-polymorphiccomponents since media often have different interfaces. It alsoemphasizes process-oriented concurrency that often exists at thetop-level of a system, and de-emphasizes the construction ofhierarchical models. The abstract semantics that binds most Ptolemy domains (with theexception of PN and CSP) is significantly different. Instead ofprocesses, components are actors with three-phase firings. Theobjective of this abstract semantics is to be able to define "domainpolymorphic" actors, which are actors that operate in several models ofcomputation. This enables hierarchically composing distinct models ofcomputation, since an aggregation of actors in one domain becomes anactor in another. No such composition is possible (by any method weknow of) with processes. Indeed, both PN and CSP do not compose wellwith other domains. There is no useful way to embed PN or CSP modelswithin other, firing-based models of computation. A key reason for the choice of abstract semantics in Metropolis is thedesire to model several aspects of a system, including particularly itsperformance when mapped to hardware resources. The separate threads ofcontrol model parallel hardware systems well, and mesh well with trendsin hardware design. Processes in Metropolis are defined in a Java-like syntax, and use amodel of computation in which components are processes with globalsynchronization points. Constraints are an explicit, declarative mannerto specify requirements on performance (e.g. power or timing) andsharing of computation and communication resources. For example, timingconstraints are expressed in linear temporal logic and timed logic. Avariety of back-ends have been built or are under construction, toperform simulation, formal verification and synthesis, including onesthat target Java, SystemC, and C. By contrast, in Ptolemy, actors are defined in ordinary Java. Moreeasily retargetted actor-definition languages are under development,including Cal ( ).and Actif( ). One of the key innovations in Metropolis is the notion of "quantitymanagers." Quantity managers contain code that is invoked when arequest is made to annotate a process transition with a quantity, suchas time, energy, or memory. Such requests are made, for example, on theexecution of a statement, or on a communication action over a medium. Aspecial case of quantity manager is the global time manager, which isused to implement a discrete event semantics, where events areprocessed in chronological order. Constraints in terms of quantitiesare expressed formally in the Logic Of Constraints, a logicparticularly suitable for specifying constraints at the abstract systemlevel, where coordination of executions, not the low level interaction,is of concern. LOC is a formalism designed to reason about simulationtraces. It consists of all the terms and operators allowed insentential logic, with additions that make it possible to specifysystem level quantitative constraints. In Ptolemy, quantity managers would be associated with the director,although no director has been developed (to our knowledge) with such abroadly applicable mechanism. 2.4 What is the relationship between Ptolemy and Kepler? Ptolemy ( )and The Kepler Project ( are two separate projects. The Kepler Project FAQ saysWhat is the difference between Kepler and Ptolemy? Roughly speaking, Ptolemy aims at modeling concurrent systems, studyingsystem models, various models of computation, etc. as explainedabove. In constrast, Kepler aims at execution of scientific workflows(by end users and/or workflow engineers), inheriting modeling anddesign capabilities including the Vergil GUI and workflow schedulingand execution capabilities from Ptolemy. How does Kepler extend Ptolemy? Kepler extensions to Ptolemy include an ever increasing number of components (called actors in Ptolemy terminology) aimed particularly at scientific applications, e.g., for remote data and metadata access, data transformations, data analysis, interfacing with legacy applications, web service invocation and deployment, provenance tracking, etc. Target application areas include bioinformatics, cheminformatics, ecoinformatics, and geoinformatics workflows among others. Kepler also inherits from Ptolemy the actor-oriented modeling paradigm that separates workflow components from the overall workflow orchestration (via so-called directors), making components more easily reusable. Through actor-oriented and hierarchical modeling features built into Ptolemy, Kepler scientific workflows can operate at very different level of granularity, from low-level "plumbing workflows" that explictely move data around, start and monitor remote jobs, etc. to high-level "conceptual workflows" that interlink complex, domain specific data analysis steps.Concerning using Ptolemy actors within Kepler, Norbert Podhorszki writes:If you find a Ptolemy actor useful, just remember its class name (e.g. In Kepler, "Tools/Instantiate Component" menu allows you to type in the class name, which will put an actor instance on your canvas just as dragging one from the actor tree. The ptolemy jar is stored in the kepler.jar, so you have access to any Ptolemy actors and directors. If you want to use a director not in Kepler tree, you have to use the"Tools/Instantiate Attribute" menu. I use it to get a DDF director frequently (class I suppose, you can create a kar file for any ptolemy actor just as for kepler actors, if you want to add some of them into the Kepler actor tree.3. Installation questions 3.1 How do I downloadPtolemy II? Ptolemy II is available in several formats including applets, source code, a Windows installer and Web Start. For details, see 3.2 What platforms does Ptolemy II run under? Ptolemy II is written in Java, so it should run on any platformthat supports a recent Java Virtual machine. Locally, we useWindows XP with the Cygwin toolkit for development.The nightly builds run under Solaris 8. Some people in the group use Linux. 3.3 What do I need to Install Ptolemy II? At the minimum, you need the Java Runtime Environment.For details, see the installation pages at 3.4 How do I get Subversion access to PtolemyIISubversion access to the Ptolemy II development tree is available.Instructions can be found at 4. Using Ptolemy II 4.1 How do I invoke Ptolemy II? If you install Ptolemy II using the Windows installer, thenmenu choices should be added to Start -> Programs -> Ptolemy.Ptolemy II models can be run from the command line, this is what we dofor the nightly test suite.

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