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ptolemy II.pdf
Ptolemy II
Heterogeneous Concurrent Modeling and Design in Java
Volume 3: Ptolemy II Domains
Contents
1. DE Domain 1
1.1. Introduction 1
1.1.1. Model Time 1
1.1.2. Simultaneous events 2
1.1.3. Iteration 4
1.1.4. Starting a Model 4
1.1.5. Pure Events at the Current Time 4
1.1.6. Stopping Execution 5
1.2. Overview of The Software Architecture 5
1.3. The DE Actor Library 7
1.4. Mutations 7
1.5. Writing DE Actors 9
1.5.1. General Guidelines 9
1.5.2. Examples 12
1.5.3. Thread Actors 14
1.6. Composing DE with Other Domains 15
1.6.1. DE inside Another Domain 16
1.6.2. Another Domain inside DE 18
2. CT Domain 19
2.1. Introduction 19
2.1.1. System Specification 21
2.1.2. Time 22
2.2. Solving ODEs numerically 23
2.2.1. Basic Notations 23
2.2.2. Fixed-Point Behavior 24
2.2.3. ODE Solvers Implemented 24
2.2.4. Discontinuity 26
2.2.5. Breakpoint ODE Solvers 27
2.3. Signal Types 27
2.4. CT Actors 29
2.4.1. CT Actor Interfaces 29
2.4.2. Actor Library 29
2.4.3. Domain Polymorphic Actors 32
2.5. CT Directors 33
2.5.1. ODE Solvers 33
2.5.2. CT Director Parameters 33
2.5.3. CTMultiSolverDirector 34
2.5.4. CTMixedSignalDirector 34
2.5.5. CTEmbeddedDirector 35
2.6. Interacting with Other Domains 35
2.7. CT Domain Demos 36
2.7.1. Lorenz System 36
2.7.2. Microaccelerometer with Digital Feedback. 38
2.7.3. Sticky Point Masses System 39
2.8. Implementation 40
2.8.1. ct.kernel.util package 40
2.8.2. ct.kernel package 41
2.8.3. Scheduling 45
2.8.4. Controlling Step Sizes 46
2.8.5. Mixed-Signal Execution 47
2.8.6. Hybrid System Execution 47
3. SDF Domain 49
3.1. Purpose of the Domain 49
3.2. Using SDF 49
3.2.1. Deadlock 49
3.2.2. Consistency of data rates 51
3.2.3. How many iterations? 52
3.2.4. Granularity 52
3.3. Properties of the SDF domain 53
3.3.1. Scheduling 54
3.3.2. Hierarchical Scheduling 55
3.3.3. Hierarchically Heterogeneous Models 56
3.4. Software Architecture 56
3.4.1. SDF Director 56
3.4.2. SDF Scheduler 57
3.4.3. SDF ports and receivers 59
3.4.4. ArrayFIFOQueue 60
3.5. Actors 60
4. FSM Domain 61
4.1. Introduction 61
4.2. Building FSMs in Vergil 62
4.2.1. Alternate Mark Inversion Coder 62
4.3. The Implementation of FSMActor 64
4.3.1. Guard Expressions 64
4.3.2. Actions 66
4.3.3. Execution 66
4.4. Modal Models 67
4.4.1. A Schmidtt Trigger Example 67
4.4.2. Implementation 69
4.4.3. Applications 69
5. Giotto Domain 71
5.1. Introduction 71
5.2. Using Giotto 71
5.3. Interacting with Other Domains 74
5.3.1. Giotto Embedded in DE and CT 74
5.3.2. FSM and SDF embedded inside Giotto 76
5.4. Software structure of the Giotto Domain and implementation 77
5.4.1. GiottoDirector 78
5.4.2. GiottoScheduler 79
5.4.3. GiottoReceiver 80
5.4.4. GiottoCodeGenerator 81
6. Rendezvous Domain 83
6.1. Introduction 83
6.2. Properties of the Rendezvous Domain 84
6.2.1. Atomic Communication 84
6.2.2. Nondeterministic Choice of Possible Communications 85
6.2.3. Communication Primitives 85
6.2.4. Stop and Deadlock 85
6.3. Communication Primitives 85
6.3.1. Put-to-all and Get-from-all 86
6.3.2. Put-to-any and Get-from-any 86
6.3.3. Get-from-any-put-to-all 86
6.4. Barrier and Merge 86
6.4.1. Barrier 86
6.4.2. Merge 87
6.4.3. Combining Barrier and Merge 87
6.5. The Rendezvous Software Architecture 87
6.5.1. Class Structure 87
6.5.2. Starting the model 88
6.5.3. Atomic Communication in Concurrent Execution 90
6.5.4. Detecting Deadlocks: 90
6.6. Application to Resource Management 90
6.6.1. Resource Management Demo 90
6.6.2. ResourcePool 91
6.7. Threads in an Actor 91
6.7.1. Creating Extra Threads in an Actor 91
6.7.2. Manually Blocking and Unblocking Threads 91
7. CSP Domain 93
7.1. Introduction 93
7.2. Properties of the CSP Domain 94
7.2.1. Atomic Communication: Rendezvous 94
7.2.2. Choice: Nondeterministic Rendezvous 94
7.2.3. Deadlock 96
7.2.4. Time 96
7.2.5. Differences from Original CSP Model as Proposed by Hoare 97
7.3. Using CSP 97
7.3.1. Unconditional vs. Conditional Rendezvous 97
7.3.2. Time 99
7.4. The CSP Software Architecture 100
7.4.1. Class Structure 100
7.4.2. Starting the model 100
7.4.3. Detecting deadlocks: 102
7.4.4. Terminating the model 103
7.4.5. Pausing/Resuming the Model 103
7.5. Example CSP Applications 104
7.5.1. Dining Philosophers 104
7.5.2. Hardware Bus Contention 105
7.6. Technical Details 105
7.6.1. Rendezvous Algorithm 105
7.6.2. Conditional Communication Algorithm 106
7.6.3. Modification of Rendezvous Algorithm 110
8. DDE Domain 111
8.1. Introduction 111
8.2. Using DDE 111
8.2.1. DDEActor 112
8.2.2. DDEIOPort 112
8.2.3. Feedback Topologies 112
8.3. Properties of the DDE domain 113
8.3.1. Enabling Communication: Advancing Time 113
8.3.2. Maintaining Communication: Null Tokens 114
8.3.3. Alternative Distributed Discrete Event Methods 116
8.4. The DDE Software Architecture 117
8.4.1. Local Time Management 117
8.4.2. Detecting Deadlock 118
8.4.3. Ending Execution 118
8.5. Example DDE Applications 119
9. PN Domain 121
9.1. Introduction 121
9.2. Using PN 122
9.2.1. Deadlock in Feedback Loops 122
9.2.2. Designing Actors 122
9.3. Properties of the PN domain 122
9.3.1. Asynchronous Communication 122
9.3.2. Bounded Memory Execution 123
9.3.3. Time 123
9.3.4. Mutations 124
9.3.5. Hierarchy 124
9.4. The PN Software Architecture 124
9.4.1. PNDirector 124
9.4.2. TimedPNDirector 125
9.4.3. PNQueueReceiver 125
9.4.4. Handling Deadlock 126
9.4.5. Finite Iterations 126
9.4.6. NondeterministicMerge 126
10. PSDF Domain 127
10.1. Purpose of the Domain 127
10.2. Using PSDF 127
10.2.1. Restricted Reconfiguration 128
10.2.2. Symbolic scheduling limitations 129
10.3. Properties of the PSDF domain 129
10.3.1. Scheduling 129
10.3.2. Local Synchrony and Reconfiguration Analysis 130
10.4. Software Architecture 131
10.5. Actors 131
11. DDF Domain 133
11.1. Introduction 133
11.2. Properties of the DDF domain 133
11.2.1. Firing Rules 134
11.2.2. Scheduling 134
11.3. Software Architecture and Implementation 136
11.3.1. DDFDirector 136
11.3.2. Writing DDF Actors 137
11.4. Example DDF Applications 139
11.4.1. Conditionals with If-Else Structure 139
11.4.2. Data-Dependent Iterations 140
11.4.3. Recursion 142
12. HDF Domain 143
12.1. Introduction 143
12.2. Using HDF in Vergil 143
12.2.1. Data Rates of the Modal Model 143
12.2.2. Multi-Token Syntax in Guard Expressions 144
12.2.3. Actions in Modal Model 145
12.3. Properties of the HDF domain 145
12.3.1. Scheduling 145
12.3.2. Hierarchical Heterogeneous Models 145
12.4. Software Architecture 145
12.4.1. HDF Director 145
12.4.2. HDFFSM Director 146
12.5. Actors 146
1 DE Domain
1.1 Introduction
1.1.1 Model Time
1.1.2 Simultaneous events
FIGURE 1.1. If there are simultaneous events at B and D, then the one at B will have higher prior...
FIGURE 1.2. An example of a directed zero-delay loop.
FIGURE 1.3. A Delay actor can be used to break a zero-delay loop.
1.1.3 Iteration
1.1.4 Starting a Model
1.1.5 Pure Events at the Current Time
1.1.6 Stopping Execution
1.2 Overview of The Software Architecture
FIGURE 1.4. UML static structure diagram for the DE kernel package.
1.3 The DE Actor Library
FIGURE 1.5. The library of DE-specific actors.
1.4 Mutations
FIGURE 1.6. Topology before and after mutation for the example in figure 1.7.
FIGURE 1.7. An example of a class that constructs a model and then mutates it.
1.5 Writing DE Actors
1.5.1 General Guidelines
1.5.2 Examples
TimedDelay Actor
FIGURE 1.8. A domain-specific actor, TimedDelay actor, in DE.
Server Actor
FIGURE 1.9. Code for the Server actor. For more details, see the source code.
1.5.3 Thread Actors
FIGURE 1.10. Code listings for two style of writing the ABRecognizer actor.
FIGURE 1.11. The run() method of the ABRO actor.
1.6 Composing DE with Other Domains
FIGURE 1.12. An example of heterogeneous and hierarchical composition. The CT subsystem and DE su...
1.6.1 DE inside Another Domain
1.6.2 Another Domain inside DE
2 CT Domain
2.1 Introduction
(1)
FIGURE 2.1. Possible implementations of the system equations.
(2)
(3)
(4)
, (5)
. (6)
, (7)
(8)
2.1.1 System Specification
1. The signal-flow model is more abstract. Ptolemy II focuses on system-level design and behavior...
2. The signal flow model is more flexible and extensible, in the sense that it is easy to embed c...
3. The signal flow model is consistent with other models of computation in Ptolemy II. Most model...
4. The signal flow model is compatible with the conservation law model. For physical systems that...
FIGURE 2.2. A conceptual block diagram for continuous time systems.
FIGURE 2.3. The block diagram for the example system.
(9)
2.1.2 Time
2.2 Solving ODEs numerically
2.2.1 Basic Notations
, (10)
, (11)
2.2.2 Fixed-Point Behavior
. (12)
(13)
(14)
, (15)
(16)
2.2.3 ODE Solvers Implemented
1. Forward Euler solver:
(17)
2. 2(3)-order Explicit Runge-Kutta solver
(18)
(19)
(20)
3. 4(5)-order Explicit Runge-Kutta solver
(21)
(22)
(23)
4. Backward Euler solver:
(24)
5. Trapezoidal Rule solver:
. (25)
2.2.4 Discontinuity
2.2.5 Breakpoint ODE Solvers
2.3 Signal Types
FIGURE 2.4. A signal type lattice.
2.4 CT Actors
2.4.1 CT Actor Interfaces
2.4.2 Actor Library
(26)
(27)
(28)
2.4.3 Domain Polymorphic Actors
2.5 CT Directors
2.5.1 ODE Solvers
2.5.2 CT Director Parameters
Table 13: CTDirector Parameters
2.5.3 CTMultiSolverDirector
Table 14: Additional Parameter for CTMultiSolverDirector
2.5.4 CTMixedSignalDirector
Table 15: Additional Parameter for CTMixedSignalDirector
2.5.5 CTEmbeddedDirector
2.6 Interacting with Other Domains
FIGURE 2.5. Embedding a DE component in a CT system.
FIGURE 2.6. Embedding a CT component in a DE system.
FIGURE 2.7. Hybrid system modeling.
2.7 CT Domain Demos
2.7.1 Lorenz System
(29)
FIGURE 2.8. Block diagram for the Lorenz system.
FIGURE 2.9. The simulation result of the Lorenz system.
2.7.2 Microaccelerometer with Digital Feedback.
FIGURE 2.10. Micro-accelerator with digital feedback
FIGURE 2.11. Block diagram for the micro-accelerator system.
FIGURE 2.12. Execution result of the microaccelerometer system.
2.7.3 Sticky Point Masses System
FIGURE 2.13. Sticky point masses system
FIGURE 2.14. Modeling sticky point masses.
FIGURE 2.15. The simulation result of the sticky point masses system.
2.8 Implementation
FIGURE 2.16. The packages in the CT domain.
2.8.1 ct.kernel.util package
FIGURE 2.17. UML for ct.kernel.util package.
2.8.2 ct.kernel package
FIGURE 2.18. UML for ct.kernel package, actor related classes.
FIGURE 2.19. UML for ct.kernel package, director related classes.
FIGURE 2.20. UML for ct.kernel.solver package.
2.8.3 Scheduling
1. Given the state of the system at time points , if the current integration step size is , i.e. ...
2. After the new state is computed, test whether this step is successful. Local truncation error ...
3. If the step is successful, predict the next step size. Otherwise, reduce the step size and try...
FIGURE 2.21. A chain of integrators.
2.8.4 Controlling Step Sizes
. (30)
2.8.5 Mixed-Signal Execution
DE inside CT
CT inside DE
(31)
2.8.6 Hybrid System Execution
Appendix A: Brief Mathematical Background
Theorem 1. [Existence and uniqueness of the solution of an ODE
. (32)
1. [Continuity Condition] Let D be the set of possible discontinuity points; it may be empty. For...
2. [Lipschitz Condition] There is a piecewise continuous bounded function :, where is the set of ...
. (33)
(34)
. (35)
u
Theorem 2. [Contraction Mapping Theorem.
(36)
3 SDF Domain
3.1 Purpose of the Domain
3.2 Using SDF
3.2.1 Deadlock
FIGURE 3.1. An SDF model that deadlocks.
FIGURE 3.2. The model of figure 3.1 corrected with an instance of SampleDelay in the feedback loop.
3.2.2 Consistency of data rates
FIGURE 3.3. An SDF model with inconsistent rates.
FIGURE 3.4. Figure 3.3 modified to have consistent rates.
3.2.3 How many iterations?
FIGURE 3.5. A model that plots the Fast Fourier Transform of a signal. Only one iteration must be...
FIGURE 3.6. A model that plots the values of a signal. 256 iterations must be executed to plot th...
3.2.4 Granularity
FIGURE 3.7. A model that implements a block FIR filter. The vectorizationFactor parameter of the ...
3.3 Properties of the SDF domain
3.3.1 Scheduling
FIGURE 3.8. An example SDF model. The model has a toplevel named E0, an SDF Director named D1 and...
Firings(A) ¥ ProductionRate(A1) = Firings(B) ¥ ConsumptionRate(B1)
Firings(A) ¥ ProductionRate(A2) = Firings(C) ¥ ConsumptionRate(C1)
Firings(C) ¥ ProductionRate(C2) = Firings(B) ¥ ConsumptionRate(B2)
FIGURE 3.9. A consistent cyclic graph, properly annotated with delays. A one token delay is repre...
FIGURE 3.10. Two models, with each port annotated with the appropriate rate properties. The model...
3.3.2 Hierarchical Scheduling
3.3.3 Hierarchically Heterogeneous Models
3.4 Software Architecture
FIGURE 3.11. The static structure of the SDF kernel classes.
3.4.1 SDF Director
3.4.2 SDF Scheduler
FIGURE 3.12. The sequence of method calls during scheduling of a hierarchical model.
Multiports
Dangling ports
3.4.3 SDF ports and receivers
3.4.4 ArrayFIFOQueue
3.5 Actors
4 FSM Domain
4.1 Introduction
4.2 Building FSMs in Vergil
4.2.1 Alternate Mark Inversion Coder
1. Start Vergil, open a graph editor by selecting File -> New -> Graph Editor.
2. From MoreLibraries/Automata in the palette on the left, drag an FSM actor to the graph. Rename...
3. Right click on AMICoder, select Customize -> Ports. Add an input port with name in and an outp...
4. Right click on AMICoder, select Open Actor. This will open an FSM editor for AMICoder. Note th...
5. From the palette on the left, drag a state to the graph, rename it Positive. Drag another stat...
6. Control-drag from the Positive state to the Negative state to create a transition.
7. Double click on the transition. This will bring up the dialog box shown in figure 4.1 for edit...
FIGURE 4.1. The dialog box for editing parameters of a transition.
8. Set guardExpression to in==1, and outputActions to out=1 and hit the Commit button.
9. Create a transition from the Positive state back to itself with guard expression in==0 and o...
10. Create a transition from the Negative state back to itself with guard expression in==0 and ...
11. Create a transition from the Negative state to the Positive state with guard expression in==...
12. The construction of AMICoder is complete. It will look like what is shown in figure 4.2.
FIGURE 4.2. Vergil FSM editor showing the AMICoder.
13. Return to the graph editor opened in step 1.
14. Drag a Pulse actor (from Actors/Sources/SequenceSources), a SequencePlotter (from Actors/ Sin...
15. Connect the actors as shown in figure 4.3.
FIGURE 4.3. An SDF model with the AMICoder.
16. Edit parameters of the Pulse actor: set indexes to {0,1,2,3,4,5}; set values to {0,1,1...
17. The model construction is complete.
18. Select View -> Run Window from the menu. Set director iterations to 6 and execute the model. ...
4.3 The Implementation of FSMActor
FIGURE 4.4. The UML static structure diagram of FSMActor-related classes.
4.3.1 Guard Expressions
4.3.2 Actions
4.3.3 Execution
4.4 Modal Models
FIGURE 4.5. A modal model example.
4.4.1 A Schmidtt Trigger Example
1. Open a Vergil graph editor. From Actors/HigherOrderActors, drag a ModalModel actor to the grap...
2. Look inside SchmidttTrigger. This will open an FSM editor for the mode controller. Construct a...
FIGURE 4.6. The mode controller for SchmidttTrigger.
3. Right click on the state named P, select Add Refinement. Specify the name of the refinement as...
FIGURE 4.7. Model for the refinements in SchmidttTrigger. RefinementP has Const set to 1.0, Refin...
4. Add a refinement named RefinementN to state N. Build a model for it similar to the one shown i...
5. Back to the graph editor opened in step 1. Build the model as shown in figure 4.8. The model g...
FIGURE 4.8. The top-level model with the SchmidttTrigger.
6. Run the model for 200 iterations. A sample result is shown in figure 4.9.
FIGURE 4.9. Sample result of the model shown in figure 4.8.
4.4.2 Implementation
FIGURE 4.10. FSM kernel classes that support modal models.
1. The FSM director transfers the input tokens from the outside domain to the mode controller and...
2. The preemptive transitions from the current state of the mode controller are examined. If ther...
3. Fire the refinement of the current state.
4. The non-preemptive transitions from the current state of the mode controller are examined. If ...
5. Any output token produced by the mode controller or the refinement is transferred to the outsi...
1. Execute the commit actions of the transition.
2. Set the current state of the mode controller to the destination state of the transition.
3. If the value of the reset parameter of the transition is true, the refinement of the destinati...
4.4.3 Applications
Hybrid System Modeling
Multirate System Modeling
Communication Protocol Modeling
5 Giotto Domain
5.1 Introduction
5.2 Using Giotto
FIGURE 5.1. A Simple Giotto model with only one mode.
FIGURE 5.2. Simulation results for the model in Figure 5.1
FIGURE 5.3. Generated Giotto code for the model in Figure 5.1
5.3 Interacting with Other Domains
5.3.1 Giotto Embedded in DE and CT
FIGURE 5.4. Giotto model embedded in DE model.
FIGURE 5.5. Simulation results of model of Figure 5.4
5.3.2 FSM and SDF embedded inside Giotto
FIGURE 5.6. Modal model embedded in Giotto model.
5.4 Software structure of the Giotto Domain and implementation
FIGURE 5.7. Simulation results for model in Figure 5.6.
5.4.1 GiottoDirector
FIGURE 5.8. The static structure of the Giotto package kernel classes.
5.4.2 GiottoScheduler
FIGURE 5.9. Schedule computation of GiottoScheduler.
5.4.3 GiottoReceiver
FIGURE 5.10. Working mechanism of GiottoReceiver.
5.4.4 GiottoCodeGenerator
6 Rendezvous Domain
6.1 Introduction
6.2 Properties of the Rendezvous Domain
6.2.1 Atomic Communication
FIGURE 6.1. Illustrating how processes block waiting to rendezvous
6.2.2 Nondeterministic Choice of Possible Communications
6.2.3 Communication Primitives
6.2.4 Stop and Deadlock
6.3 Communication Primitives
6.3.1 Put-to-all and Get-from-all
6.3.2 Put-to-any and Get-from-any
6.3.3 Get-from-any-put-to-all
6.4 Barrier and Merge
6.4.1 Barrier
FIGURE 6.2. The Barrier actor
6.4.2 Merge
FIGURE 6.3. The Merge actor
6.4.3 Combining Barrier and Merge
FIGURE 6.4. Using a Barrier and a Merge to express complex synchronization logic
6.5 The Rendezvous Software Architecture
6.5.1 Class Structure
FIGURE 6.5. Static structure diagram for classes in the Rendezvous kernel.
6.5.2 Starting the model
FIGURE 6.6. Sequence of steps involved in setting up and controlling the model.
6.5.3 Atomic Communication in Concurrent Execution
6.5.4 Detecting Deadlocks:
6.6 Application to Resource Management
6.6.1 Resource Management Demo
6.6.2 ResourcePool
6.7 Threads in an Actor
6.7.1 Creating Extra Threads in an Actor
6.7.2 Manually Blocking and Unblocking Threads
7 CSP Domain
7.1 Introduction
7.2 Properties of the CSP Domain
7.2.1 Atomic Communication: Rendezvous
FIGURE 7.1. Illustrating how processes block waiting to rendezvous
7.2.2 Choice: Nondeterministic Rendezvous
CIF:
CDO:
FIGURE 7.2. Example of how a CDO might be used in a buffer.
7.2.3 Deadlock
7.2.4 Time
7.2.5 Differences from Original CSP Model as Proposed by Hoare
7.3 Using CSP
7.3.1 Unconditional vs. Conditional Rendezvous
FIGURE 7.3. Template for executing a CDO construct.
FIGURE 7.4. Code used to implement the buffer process described in figure 7.3.
7.3.2 Time
7.4 The CSP Software Architecture
7.4.1 Class Structure
FIGURE 7.5. Static structure diagram for classes in the CSP kernel.
CSPDirector:
CSPReceiver:
CSPActor:
ConditionalReceive, ConditionalSend:
7.4.2 Starting the model
FIGURE 7.6. Sequence of steps involved in setting up and controlling the model.
FIGURE 7.7. Code executed by ProcessThread.run().
7.4.3 Detecting deadlocks:
7.4.4 Terminating the model
7.4.5 Pausing/Resuming the Model
7.5 Example CSP Applications
7.5.1 Dining Philosophers
Nondeterministic Resource Contention
FIGURE 7.8. Illustration of the dining philosophers problem.
7.5.2 Hardware Bus Contention
Deterministic Resource Contention
FIGURE 7.9. Illustration of the Hardware Bus Contention example.
7.6 Technical Details
7.6.1 Rendezvous Algorithm
FIGURE 7.10. Rendezvous algorithm.
7.6.2 Conditional Communication Algorithm
Built on top of rendezvous:
FIGURE 7.11. Conceptual view of how conditional communication is built on top of rendezvous.
Choosing which branch succeeds
Algorithm used by each branch:
FIGURE 7.12. Algorithm used to determine if a conditional rendezvous branch succeeds or fails
7.6.3 Modification of Rendezvous Algorithm
FIGURE 7.13. Modification of rendezvous algorithm, section 7.6.3, shown in ellipse.
8 DDE Domain
8.1 Introduction
8.2 Using DDE
8.2.1 DDEActor
getNextToken()
getLastPort()
8.2.2 DDEIOPort
8.2.3 Feedback Topologies
FIGURE 8.1. Initializing feedback topologies.
8.3 Properties of the DDE domain
8.3.1 Enabling Communication: Advancing Time
Communicating Tokens
Communicating Time
FIGURE 8.2. DDE actors and local time.
8.3.2 Maintaining Communication: Null Tokens
FIGURE 8.3. Timed deadlock (feedforward).
FIGURE 8.4. Timed deadlock (feedback).
Preventing Feedforward Timed Deadlock
Preventing Feedback Timed Deadlock
8.3.3 Alternative Distributed Discrete Event Methods
8.4 The DDE Software Architecture
8.4.1 Local Time Management
FIGURE 8.5. Key classes for managing time locally.
8.4.2 Detecting Deadlock
FIGURE 8.6. Additional classes in the DDE kernel.
8.4.3 Ending Execution
8.5 Example DDE Applications
FIGURE 8.7. Localized Zeno condition topology.
9 PN Domain
9.1 Introduction
9.2 Using PN
9.2.1 Deadlock in Feedback Loops
9.2.2 Designing Actors
9.3 Properties of the PN domain
9.3.1 Asynchronous Communication
9.3.2 Bounded Memory Execution
9.3.3 Time
1. The process is delayed and is explicitly waiting for time to advance (delay block).
2. The process is waiting for data to arrive on one of its input channels (read block).
9.3.4 Mutations
9.3.5 Hierarchy
9.4 The PN Software Architecture
FIGURE 9.1. Static structure of the PN kernel.
9.4.1 PNDirector
9.4.2 TimedPNDirector
9.4.3 PNQueueReceiver
9.4.4 Handling Deadlock
9.4.5 Finite Iterations
9.4.6 NondeterministicMerge
10 PSDF Domain
10.1 Purpose of the Domain
10.2 Using PSDF
10.2.1 Restricted Reconfiguration
FIGURE 10.1. A PSDF model that is not locally synchronous.
FIGURE 10.2. The model of figure 10.1 corrected using hierarchy.
10.2.2 Symbolic scheduling limitations
10.3 Properties of the PSDF domain
10.3.1 Scheduling
FIGURE 10.3. An example SDF model.
Firings(A) ¥ ProductionRate(A1) = Firings(B) ¥ ConsumptionRate(B1)
Firings(A) ¥ ProductionRate(A2) = Firings(C) ¥ ConsumptionRate(C1)
Firings(C) ¥ ProductionRate(C2) = Firings(B) ¥ ConsumptionRate(B2)
Firings(A) = ConsumptionRate(B1) / (gcd(ConsumptionRate(C1) * ProductionRate(A1) / gcd(Production...
10.3.2 Local Synchrony and Reconfiguration Analysis
10.4 Software Architecture
10.5 Actors
11 DDF Domain
11.1 Introduction
11.2 Properties of the DDF domain
11.2.1 Firing Rules
11.2.2 Scheduling
1. After any finite time the token sequence (including consumed tokens) on any channel is a prefi...
2. The scheduler should be able to execute a graph forever if it is possible to execute a graph f...
3. The scheduler should be able to execute a graph forever in bounded memory if it is possible to...
4. The scheduler should execute the graph in a sequence of well-defined and determinate iteration...
FIGURE 11.1. The pseudo-code of the scheduling algorithm implemented in the DDF domain.
11.3 Software Architecture and Implementation
11.3.1 DDFDirector
11.3.2 Writing DDF Actors
FIGURE 11.2. Initialization code of DDFBooleanSelect actor.
FIGURE 11.3. Split-phase firing code of DDFBooleanSelect actor.
FIGURE 11.4. Rate update code of DDFBooleanSelect actor.
FIGURE 11.5. Initialization of ArrayTokens and their exemplary uses for the DDFSelect actor.
11.4 Example DDF Applications
11.4.1 Conditionals with If-Else Structure
FIGURE 11.6. A model illustrating if-then-else structure.
11.4.2 Data-Dependent Iterations
FIGURE 11.7. A model illustrating do-while structure.
11.4.3 Recursion
FIGURE 11.8. A model illustrating recursion structure for computing prime numbers.
12 HDF Domain
12.1 Introduction
12.2 Using HDF in Vergil
12.2.1 Data Rates of the Modal Model
FIGURE 12.1. An HDF model example.
12.2.2 Multi-Token Syntax in Guard Expressions
12.2.3 Actions in Modal Model
12.3 Properties of the HDF domain
12.3.1 Scheduling
12.3.2 Hierarchical Heterogeneous Models
12.4 Software Architecture
12.4.1 HDF Director
12.4.2 HDFFSM Director
12.5 Actors
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Index
Symbols
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
Z
Heterogeneous Concurrent Modeling and Design in
Java (Volume 3: Ptolemy II Domains)
Christopher Brooks
Edward A. Lee
Xiaojun Liu
Stephen Neuendorffer
Yang Zhao
Haiyang Zheng
Electrical Engineering and Computer Sciences
University of California at Berkeley
Technical Report No. UCB/EECS-2008-37
http://www.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-37.html
April 15, 2008
Copyright © 2008, by the author(s).
All rights reserved.
Permission to make digital or hard copies of all or part of this work for
personal or classroom use is granted without fee provided that copies are
not made or distributed for profit or commercial advantage and that copies
bear this notice and the full citation on the first page. To copy otherwise, to
republish, to post on servers or to redistribute to lists, requires prior specific
permission.
Acknowledgement
This work was supported in part by the Center for Hybrid and Embedded
Software Systems (CHESS) at University of California, Berkeley, which
receives support from the National Science Foundation (NSF awards
#0720882 (CSR-EHS: PRET), #0647591 (CSR-SGER), and #0720841
(CSR-CPS)), the U. S. Army Research Office (ARO #W911NF-07-2-0019),
the U. S. Air Force Office of Scientific Research (MURI #FA9550-06-0312),
the Air Force Research Lab (AFRL), the State of California Micro Program,
and the following companies: Agilent, Bosch, HSBC, Lockheed-Martin,
National Instruments, and Toyota.
PTOLEMY II
HETEROGENEOUS
CONCURRENT
MODELING AND
DESIGN IN JAVA
Edited by:
Christopher Brooks, Edward A. Lee, Xiaojun Liu, Steve
Neuendorffer, Yang Zhao, Haiyang Zheng
VOLUME 3: PTOLEMY II DOMAINS
Authors:
Shuvra S. Bhattacharyya
Christopher Brooks
Elaine Cheong
John Davis, II
Mudit Goel
Bart Kienhuis
Edward A. Lee
Man-Kit Leung
Jie Liu
Xiaojun Liu
Lukito Muliadi
Steve Neuendorffer
John Reekie
Neil Smyth
Jeff Tsay
Brian Vogel
Winthrop Williams
Yuhong Xiong
Yang Zhao
Haiyang Zheng
Gang Zhou
Department of Electrical Engineering and Computer Sciences
University of California at Berkeley
http://ptolemy.eecs.berkeley.edu
R
E
V
I
N
U
E
H
A
L
E
T
T
T
H
ERE B E
186 8
Document Version 7.0
for use with Ptolemy II 7.0
April 1, 2008
I T Y OF
C
S
A
L
I
F
O
R
N
IA
LIGH T
Earlier versions:
• UCB/EECS-2007-9, UCB/ERL M05/23, UCB/ERL M04/17,
UCB/ERL M03/29, UCB/ERL M02/23, UCB/ERL M01/12,
UCB/ERL M99/40
This work was supported in part by the Center for Hybrid and Embed-
ded Software Systems (CHESS) at University of California, Berkeley,
which receives support from the National Science Foundation (NSF
awards #0720882 (CSR-EHS: PRET), #0647591 (CSR-SGER), and
#0720841 (CSR-CPS)), the U. S. Army Research Office (ARO
#W911NF-07-2-0019), the U. S. Air Force Office of Scientific Research
(MURI #FA9550-06-0312), the Air Force Research Lab (AFRL), the
State of California Micro Program, and the following companies: Agi-
lent, Bosch, HSBC, Lockheed-Martin, National Instruments, and Toyota.
Copyright © 1998-2008 The Regents of the University of California.
All rights reserved.
“Java” is a registered trademark of Sun Microsystems.
VOLUME 3
PTOLEMY II DOMAINS
This volume describes Ptolemy II domains. The domains implement models of computation, which are
summarized in chapter 1. Most of these models of computation can be viewed as a framework for com-
ponent-based design, where the framework defines the interaction mechanism between the compo-
nents. Some of the domains (CSP, Rendezvous, DDE, and PN) are thread-oriented, meaning that the
components implement Java threads. These can be viewed, therefore, as abstractions upon which to
build threaded Java programs. These abstractions are much easier to use (much higher level) than the
raw threads and monitors of Java. Others (CT, DE, SDF) of the domains implement their own schedul-
ing between actors, rather than relying on threads. This usually results in much more efficient execu-
tion. The Giotto domain, which addresses real-time computation, is not threaded, but has concurrency
features similar to threaded domains. The FSM domain is in a category by itself, since in it, the compo-
nents are not producers and consumers of data, but rather are states. The non-threaded domains are
described first, followed by FSM and Giotto, then the threaded domains followed by two newer
domains, HDF and DDF.
Volume 1 is an introduction to Ptolemy II, including tutorials on use of the software, and volume 2
describes the Ptolemy II software architecture.
This page intentional left mostly blank.
Contents
Volume 3
Ptolemy II Domains 3
Contents 5
1. DE Domain 1
1.1. Introduction 1
Simultaneous events 2
Iteration 4
Starting a Model 4
1.1.1. Model Time 1
1.1.2.
1.1.3.
1.1.4.
1.1.5. Pure Events at the Current Time 4
1.1.6.
Stopping Execution 5
1.2. Overview of The Software Architecture 5
1.3. The DE Actor Library 7
1.4. Mutations 7
1.5. Writing DE Actors 9
1.5.1. General Guidelines 9
1.5.2. Examples 12
1.5.3. Thread Actors 14
1.6. Composing DE with Other Domains 15
1.6.1. DE inside Another Domain 16
1.6.2. Another Domain inside DE 18
2. CT Domain 19
2.1. Introduction 19
System Specification 21
2.1.1.
2.1.2. Time 22
2.2. Solving ODEs numerically 23
2.2.1. Basic Notations 23
2.2.2. Fixed-Point Behavior 24
2.2.3. ODE Solvers Implemented 24
2.2.4. Discontinuity 26
2.2.5. Breakpoint ODE Solvers 27
2.3. Signal Types 27
2.4. CT Actors 29
2.4.1. CT Actor Interfaces 29
2.4.2. Actor Library 29
2.4.3. Domain Polymorphic Actors 32
2.5. CT Directors 33
2.5.1. ODE Solvers 33
2.5.2. CT Director Parameters 33
2.8. Implementation 40
ct.kernel.util package 40
ct.kernel package 41
Scheduling 45
2.8.1.
2.8.2.
2.8.3.
2.8.4. Controlling Step Sizes 46
2.8.5. Mixed-Signal Execution 47
2.8.6. Hybrid System Execution 47
Appendix: Brief Mathematical Background 48
3. SDF Domain 49
3.1. Purpose of the Domain 49
3.2. Using SDF 49
3.2.1. Deadlock 49
3.2.2. Consistency of data rates 51
3.2.3. How many iterations? 52
3.2.4. Granularity 52
3.3. Properties of the SDF domain 53
Scheduling 54
3.3.1.
3.3.2. Hierarchical Scheduling 55
3.3.3. Hierarchically Heterogeneous Models 56
2.5.3. CTMultiSolverDirector 34
2.5.4. CTMixedSignalDirector 34
2.5.5. CTEmbeddedDirector 35
2.6. Interacting with Other Domains 35
2.7. CT Domain Demos 36
2.7.1. Lorenz System 36
2.7.2. Microaccelerometer with Digital Feedback. 38
2.7.3.
Sticky Point Masses System 39
3.4. Software Architecture 56
SDF Director 56
SDF Scheduler 57
SDF ports and receivers 59
3.4.1.
3.4.2.
3.4.3.
3.4.4. ArrayFIFOQueue 60
3.5. Actors 60
4. FSM Domain 61
4.1. Introduction 61
4.2. Building FSMs in Vergil 62
4.2.1. Alternate Mark Inversion Coder 62
4.3. The Implementation of FSMActor 64
4.3.1. Guard Expressions 64
4.3.2. Actions 66
4.3.3. Execution 66
4.4. Modal Models 67
4.4.1. A Schmidtt Trigger Example 67
4.4.2.
4.4.3. Applications 69
Implementation 69
5. Giotto Domain 71
5.1. Introduction 71
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