Specifications Part 2

Transcription

1 pm4 12 Specifications Part 2 Embedded System Design Kluwer Academic Publisher by Peter Marwedel TU Dortmund 2008/11/15 ine Marwedel, 2003 Graphics: Alexandra Nolte, Ges Models of computation Communication/ Computations Shared memory Message passing Synchronous Asynchronous Communicating StateCharts SDL Finite State Machines Data flow model Computational graphs Not useful Simulink Kahn process networks SDF Sequence diagram Petri nets Von Neumann model C, C++, Java C, C++, Java with libraries CSP, ADA Discrete event (DE) model VHDL, Verilog Only experimental systems, e.g. distributed DE in Ptolemy 12,

2 Data Flow Models 12, Summary Data flow model of computation Motivation Kahn process networks SDF Visual programming languages Simulink 12,

3 Data flow as a natural model of applications Registering for courses Examples Video on demand system , Data flow modeling Definition: The process of identifying, modeling and documenting how data moves around an information system. Data flow modeling examines processes (activities that transform data from one form to another), data stores (the holding areas for data), external entities (what sends data into a system or receives data from a system, and data flows (routes by which data can flow). See also S. Edwards: ~sedwards/classes/2001/w /presentations/dataflow.ppt 12,

4 Reference model for data flow: Kahn process networks For asynchronous message passing: communication between tasks is buffered Special case: Kahn process networks: executable task graphs; Communication via infinitely large FIFOs 12, Properties of Kahn process networks (1) Each node corresponds to one program/task; Communication is only via channels; Channels include FIFOs as large as needed; Channels transmit information within an unpredictable but finite amount of time; Mapping from 1 input seq. to 1 output sequence; In general, execution times are unknown; Send operations are non-blocking Reads are blocking. One producer and one consumer; i.e. there is only one sender per channel; 12,

5 Properties of Kahn process networks (2) There is only one sender per channel. A process cannot check whether data is available before attempting a read. A process cannot wait for data for more than one port at a time. Therefore, the order of reads depends only on data, not on the arrival time. Therefore, Kahn process networks are deterministic; for a given input, the result will always the same, regardless of the speed of the nodes. SDL-like conflicts at FIFOs do not exist. 12, Properties of Kahn process networks (3) Model of parallel computations used in practice (@NXP) Example: Process f(in int u, in int v, out int w){ int i; bool b = true; for (;;) { i= b? wait(u) : wait(v); //wait return next token in FIFO, blocks if empty printf ( %i\n,i); send (i,w); //writes a token into a FIFO w/o blocking b =!b; } R. Gupta (UCSD), W. Wolf (Princeton), 2003 It is a challenge to schedule KPNs without accumulating tokens Animation 12, 2008 levi animation

6 Asynchronous message passing: Synchronous data flow (SDF) Asynchronous message passing= tasks do not have to wait until output is accepted. Synchronous data flow = all tokens are consumed at the same time. SDF model allows static scheduling of token production and consumption. In the general case, buffers may be needed at edges. 12, Synchronous Dataflow (SDF) Fixed Production/Consumption Rates Balance equations (one for each channel): f N f M A = Schedulable statically Decidable: buffer memory requirements deadlock B number of tokens consumed number of firings per iteration number of tokens produced fire A { produce N } N channel M fire B { consume M } Source: ptolemy.eecs.berkeley.edu/presentations/03/streamingeal.ppt 12,

7 Parallel Scheduling of SDF Models SDF is suitable for automated mapping onto parallel processors and synthesis of parallel circuits. A B D C Many scheduling optimization problems can be formulated. Some can be solved, too! Sequential 12, 2008 Parallel Source: ptolemy.eecs.berkeley.edu/presentations/03/streamingeal.ppt Similar MoC: Simulink - example - Semantics? Simulink uses an idealized timing model for block execution and communication. Both happen infinitely fast at exact points in simulated time. Thereafter, simulated time is advanced by exact time steps. All values on edges are constant t in between time steps. [Nicolae Marian, Yue Ma] From ess/helpdesk/help/toolbox/ fuzzy/fuzzyt25.shtml 12,

8 Starting point for model-based design Code automatically generated 12, MathWorks, cmsimages/rt_forloop_code_wl_7430.gif Summary Data flow model of computation Motivation Kahn process networks SDF Visual programming languages Simulink 12,

9 Models of computation Communication/ Computations Shared memory Message passing Synchronous Asynchronous Communicating StateCharts SDL Finite State Machines Data flow model Computational graphs Not useful Simulink Kahn process networks SDF Sequence diagram Petri nets Von Neumann model C, C++, Java C, C++, Java with libraries CSP, ADA Discrete event (DE) model VHDL, Verilog Only experimental systems, e.g. distributed DE in Ptolemy 12, Computational Graphs 12,

10 From data flow to computational graphs Pure data flow frequently too restrictive: lack of modeling control, resources etc. Modern computers contain subsystems build on the data flow paradigm (scoreboard, Tomasulo s algorithm) However, Lunatics (S. Edwards) tried to build general purpose data flow computers, but failed Data flow graphs are a special case of the somewhat more general computational graphs. Petri nets + MSCs + 12, Computational graphs in UML: Sequence Diagram Graphical means for representing sequences; time used vertically, geographical distribution horizontally. 12, deliverable

11 (Message) Sequence Charts (MSC) No distinction between accidental overlap and synchronization 12, Time/distance diagrams as a special case ck.ch 12,

12 1997. (Message) Sequence Charts PROs: Appropriate for visualizing schedules, Proven method for representing schedules in transportation. Standard defined: ITU-TS Recommendation Z.120: Message Sequence Chart (MSC), ITU-TS, Geneva, Semantics also defined: ITU-TS Recommendation Z.120: Message Sequence Chart (MSC) Annex B: Algebraic Semantics of Message Sequence Charts, ITU-TS, Geneva. CONS: describes just one case, no timing i tolerances: "What does an MSC specification mean: does it describe all behaviors of a system, or does it describe a set of sample behaviors of a system? * * H. Ben-Abdallah and S. Leue, Timing constraints in message sequence chart specifications, in Proc. 10th International Conference on Formal Description Techniques FORTE/PSTV 97, Chapman and Hall, 12, Computational UML: Activity diagram Extended Petri nets. Include decisions (like in flow charts). Graphical notation similar to SDL. Cris Kobryn: UML 2001: A Standardization Odyssey, CACM, October, , 2008 swimlane

13 UML diagrams 12, Timing diagrams Can be used to show the change of the state of an object over time. Scott Ambler, Agile Modeling, // ing.com, ,

14 UML for real-time? Initially not designed for real-time. Initially lacking features: Partitioning i of software into tasks and processes specifying timing specification of hardware components Projects on defining real-time UML based on previous work ROOM [Selic] is an object-oriented o e ted methodology ogy for real- time systems developed originally at Bell-Northern Research. UML profile for schedulability, performance and time 12, , 2008 SoC=system on a chip

15 Example: Activity diagram with annotations [ See also W. Müller et al.: UML for SoC, 12, ,

16 Task graphs Many applications can be specified in the form of a set of communicating processes. Example: system with two sensors: temperature sensor humidity sensor mux Alternating read loop read_temp; read_humi until false; of the two sensors no the right approach. FIFO 12, The case for multi-process modeling MODULE main; PROCESS get_humidity; TYPE some_channel = VAR sample : some_sample; (temperature, humidity); BEGIN some_sample : RECORD LOOP value : integer; sample.value := new_humidity line : some_channel sample.line := humidity; END; to_fifo(sample); PROCESS get_temperature; VAR sample : some_sample; END BEGIN END get _ humidity; LOOP sample.value := new_temperature; BEGIN IF sample.value > 30 THEN... get_temperature; get_humidity sample.line := temperature; END; Blocking calls new_temperature, new_humidity How to model Structure to_fifo(sample); clearer than alternating checks for dependencies between END new values in a single process tasks/processes? ,

17 Dependences between processes/tasks Get_temperature main FIFO Get_ humidity 12, Task graphs Sequence constraint Nodes are assumed to be a program described in some programming language, e.g. C or Java. Def.: A dependence graph is a directed graph G=(V,E) in which E V V is a partial order. If (v1, v2) E, then v1 is called an immediate predecessor of v2 and v2 is called an immediate successor of v1. Suppose E* is the transitive closure of E. If (v1, v2) E*, then v1 is called a predecessor of v2 and v2 is called a successor of v1. 12,

18 Task graphs 1. Timing information - Task graphs may contain additional information, for example: Timing information Arrival time deadline ] 12, Task graphs 2. I/O-information 12,

19 Task graphs 3. Shared resources 12, Task graphs 4. Hierarchical task graphs - 12,

20 Multi-thread graphs (IMEC) Def.: A multi-thread graph M is defined as an 11-tuple (O, E, V, D, ϑ, ι, Λ, E lat, E resp, i, av ) with: O: set of operation nodes, E: set of control edges, V, D : refer to the access of variables, ι: is the set of input/output nodes, Λ: associates execution latency intervals with all threads, E lat, E resp, i, av are timing constraints. 12, MTG graphs: graphical notation 12,

21 Generalization of data flow: Computational graphs Example: Petri nets Introduced in 1962 by Carl Adam Petri in his PhD thesis. Focus on modeling causal dependencies; no global l synchronization assumed (message passing only). Key elements: Conditions Either met or no met. Events May take place if certain conditions are met. Flow relation Relates conditions and events. Conditions, events and the flow relation form a bipartite graph (graph with two kinds of nodes). 12, Example: Synchronization at single track rail segment Precondition s 12,

22 Playing the token game 12, 2008 use normal view mode! Conflict for resource track 12,

23 More complex example (1) Thalys trains between Cologne, Amsterdam, Brussels and Paris. [ 12, More complex example (2) Slightly simplified: Synchronizatio n at Brussels and Paris, using stations Gare du Nord and Gare de Lyon at Paris s 12, 2008 use normal view mode!

24 Summary More computational graphs: (Message) sequence charts Time/distance charts Activity charts Other UML graphs UML profiles Real-time UML Task graphs Petri nets 12,