Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 276 2009-10-2 276 Model-Based Design for Embedded Systems terms of the resulting language. We have tested this simulation approach in SystemC 2.0 [49], Java [3], and C++ with a thread library. In addition, we have devised a service-based formalism [62] that can effectively integrate models specified at different abstraction levels, in different specification lan- guages, and with different MoCs. We also enhanced our simulation tool to support the co-simulation of these heterogeneous models. Further, this service-based formalism became the foundation of the second generation of the M ETROPOLIS environment, covered in Section 10.4. 10.3.3.2 Formal Property Verification Both academia and industry have long studied formal property verification, but the state-explosion problem restricts its usefulness to protocols and other high abstraction levels. At the implementation level or other low abstraction levels, hardware and software engineers have used simulation monitors as basic tools to check simulation traces while debugging designs. Verification languages, such as Promela, which are used by the Spin model checker [28], allow only simple concurrency modeling and are not amenable to the system design specification, which requires complex syn- chronization and architecture constraints. In contrast, M ETROPOLIS,withits formal semantics, automatically generates verification models for all the lev- els of the design [15]. Our translator automatically constructs the Spin verification model from the MMM specification, taking care of all system-level constructs. For exam- ple, it can automatically generate a verification model for the example in Figure 10.2 and verify the medium’s nonoverwriting properties. Further, as the translator refines the design through structural transformation and archi- tectural mapping, it can prove more properties, including throughput and latency. This kind of property verification typically requires several minutes of computation on a 1.8 GHz Xeon machine with 1 Gbyte of memory. When the state space complexity becomes too high, M ETROPOLIS uses an approxi- mate verification and provides the user with a confidence factor on the pass- ing result. 10.3.3.3 Simulation Monitor Simulation monitors offer an attractive alternative to formal property verifi- cation. In M ETROPOLIS, designers can use logic of constraints (LOC) formulas [7] to specify quantitative properties. The system can automatically translate the specification to simulation monitors in C++ [16], thus relieving design- ers from the tedious and error-prone task of writing monitors in the simula- tor’s language. The monitors analyze the traces and report any LOC formula violations. Like any other simulation-based approach, this one can only dis- prove an LOC formula if it finds a violation—it can never prove conclusively the formula’s correctness because that would require exhaustively analyzing Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 277 2009-10-2 Platform-Based Design and Frameworks: METROPOLIS and METRO II 277 traces. The automatic trace analyzer can be used in concert with model check- ers. It can perform property verification on a single trace even when other approaches would fail because of their excessive memory and space require- ments. In our experience with applying the automatic LOC-monitor technique to large designs with complex traces, we have found that in most cases the analysis completes in minutes and consumes only hundreds of bytes of data memory to store the LOC formulas. The analysis time tends to grow linearly with the trace size, while the memory requirement remains constant regard- less of the trace size. 10.3.3.4 Quasi-Static Scheduling We have developed an automatic synthesis technique called quasi-static scheduling (QSS) [19] to schedule a concurrent specification on computa- tional resources that provide limited concurrency. The QSS considers a sys- tem to be specified as a set of concurrent processes communicating through the FIFO queues, and generates a set of tasks that are fully and statically scheduled, except for data-dependent controls that can be resolved only at runtime. A task usually results from merging parts of several processes together and shows less concurrency than the initial specification. Moreover, the QSS allows interprocess optimizations that are difficult to achieve if pro- cesses remain separated, such as replacing interprocess communication with assignments. This technique proved particularly effective and allowed us generate a production-quality code with improved performance. Applying the QSS to a significant portion of an MPEG-2 decoder resulted in a 45% increase in the overall performance. The assumptions that the QSS requires for the input specification form a subset of what the MMM can represent. Therefore, when integrating the QSS into the M ETROPOLIS framework, we addressed two main problems: how to verify if a design satisfies the required set of rules and how to convey all relevant design information to the QSS tool. We addressed the first problem by providing a library of interfaces and communication media that implement a FIFO communication model. Those parts of the design optimized with the QSS need to use these communication primitives. To convey relevant design information to the QSS, we use a back-end tool that translates a design to be scheduled with the QSS into a Petri net speci- fication, which is QSS’s underlying model. The QSS then uses the Petri net to produce a new set of processes. These new processes show no interpro- cess communication because the QSS removes it. The processes communicate with the environment using the same primitives implemented in the library. The new code can thus be directly plugged into the MMM specification as a refinement of the network selected for scheduling. Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 278 2009-10-2 278 Model-Based Design for Embedded Systems 10.4 METRO II Design Environment METRO II [21] is the successor to METROPOLIS [8]. METRO II was developed at the University of California, Berkeley, starting in 2006. The following sec- tions introduce the reader to the goals of M ETRO II, the components of the framework, and the mapping and execution semantics used. 10.4.1 Overview The second-generation METRO II framework is based on considerations derived from the limitations of M ETROPOLIS we experienced in a set of designs that were carried out in collaboration with our industrial partners. These con- siderations are as follows. 1. Heterogeneous IP import. IP providers create models using domain- specific languages and tools. Requiring a singular form of design entry in a system-level environment requires complex translation of the orig- inal specification into the new language while making sure that seman- tics is preserved. If different designs or different components within the same design can have different semantics, the heterogeneity has to be supported by the new environment. There are two main challenges that have to be addressed: wrapping and interconnecting the IP. First, IPs can be described in different languages and can have dif- ferent semantics that can be tightly related to a particular simulator. Importing the IP entails providing a way of exposing the IP interface. The user must have the necessary aids to define wrappers that medi- ate between the IP and the framework such that the behavior can be exposed in an unambiguous way. Secondly, wrapped components have to be interconnected. Even if the interfaces are exposed in a unified way, interconnecting them is not usually a straightforward process. The data and the flow of control between IP blocks must be exposed in such a way that the framework has sufficient visibility. 2. Behavior-performance orthogonalization. For design frameworks that sup- port multiple abstraction levels, different implementations of the same basic functionality may have the same behavioral representations but different costs. For instance, different processors will be abstracted into the same programmable components. What distinguishes them is the performance vs. cost trade-off. Moreover, not all metrics are considered or optimized simultaneously. It should be possible to introduce perfor- mance metrics during the design process, as the design proceeds from specification to implementation. The specification of what a component does should be independent of how long it takes or how much power it consumes to carry out a Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 279 2009-10-2 Platform-Based Design and Frameworks: METROPOLIS and METRO II 279 task. This is the reason why we introduce dedicated components, called annotators, to annotate quantities to events. A distinction has to be made between quantities used just to track the value of a specific metric of interest and quantities whose value is used for synchronization. For instance, time is used to synchronize actions and it is not merely a number that is computed based on the state evo- lution of the system. For quantities that influence the evolution of the system, special components, called schedulers, are provided to arbitrate shared resources. The separation of schedulers from annotators allows for a sim- pler specification and provides a cleaner separation between behavior and performance. As a result, instead of a two-phase execution as in M ETROPOLIS, the execution semantics become three phase. 3. Mapping specification. Mapping relates the functional and architectural models to realize the system model. The specification of this mapping must be carried out such that there is minimal modification to the func- tional and architectural models themselves. Following the PBD approach, we want to keep the functionality and the architecture separate. The implementation of the functionality on the architecture is achieved in the mapping step. In order to explore several different implementations with minimal effort, the design envi- ronment needs to provide a fast and an efficient way of mapping with- out modifying either the functional or the architectural model much. In M ETROPOLIS, this is achieved by event-level synchronization constraints, as shown in [22]. While providing a powerful way to link the models, this approach breaks the encapsulation of the models by allowing con- straints between arbitrary pairs of events and allowing access to any local variables in the scope of the events. Also, since there are no spe- cial declarative constructs for mapping, this process of finding events and setting up constraints is not easy for designers to manipulate and debug. In M ETRO II, we restrict the mapping to be at the service level, i.e., the only accessible events for synchronization constraints are the begin/end events of interface methods in function and architecture models. Also, the only accessible values are parameters and return values of the inter- face methods. This coarser granularity and a more restrictive map- ping approach maintain the IP encapsulation and make mapping more robust for designers. 10.4.2 METRO II Design Elements An initial implementation of the METRO II framework has been carried out in SystemC 2.2. The framework has been tested under Linux, Solaris, and cygwin. Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 280 2009-10-2 280 Model-Based Design for Embedded Systems sc_eventsc_module Method Port Event Interface Mapper Adaptor Component Constraint solver Annotator Scheduler Manager Implementation platform: SystemC 2.2 M ETRO II core FIGURE 10.6 Implementation of M ETRO II. The infrastructure is summarized in Figure 10.6. The sc_event and sc_module classes from SystemC are leveraged directly to derive the cor- responding event and component classes in M ETRO II. The connection and coordination of components are carried out through events. The event is a key concept in M ETRO II. It is formally defined as a tuple < p, T, V >, where p is a process that generates the event, T is a tag set, and V is a set of associated values. Tags are used to describe the semantics of the system and values are used to represent the states of the system. Methods, interfaces, and ports are built on the concept of event. A method is characterized by a pair of begin and end events. An interface contains one or more methods. Ports are associated with interfaces, and only ports with compatible interfaces can be connected. A component can have zero or more ports. To handle different aspects of the events, special objects are defined, including annotators, schedulers, and constraint solvers. Annotators anno- tate events with quantities, schedulers coordinate the execution sequence of events, and constraint solvers resolve the declarative constraints on events. Mappers and adaptors are defined to interconnect components. Mappers bridge the function methods and architecture services. Adaptors intercon- nect components with heterogeneous MoCs. Finally, the manager coordi- nates the execution of all the objects using three-phase execution semantics. Figure 10.7 illustrates the major M ETRO II elements. We attempt to use the iconography here throughout the work. A snippet of the M ETRO II code for a reader component, a mapper, a scheduler, and an annotator in a typical producer–consumer design example is shown in the figure. More details of these elements are introduced below. 10.4.2.1 Components A component is an object that encapsulates an imperative code in a design, either functional or architectural. Components interface with other Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 281 2009-10-2 Platform-Based Design and Frameworks: METROPOLIS and METRO II 281 Wrapper Component View port Required port Provided port Annotator Constraint solver Scheduler IP Event <proc, tag, value> M2_INTERFACE(i_func_receiver) { public: M2_TWOARG_PROCEDURE(receive, void *, unsigned long); }; M2_COMPONENT(Reader) { public: m2_required_port<i_func_receiver> out_port; sc_process_handle this_thread; SC_HAS_PROCESS(Reader); Reader(sc_module_name n) : m2_component(n) { SC_THREAD(main); } void main() { this_thread = sc_get_current_process_handle(); int array[3]; for (int i=0; i<5; i++) { out_port->receive(array, 3 * sizeof(int)) } } }; c_double_handshake c("rendezvous"); Writer w("Writer"); Reader r("Reader"); M2_CONNECT(r, out_port, c, read_port); M2_CONNECT(w, out_port, c, write_port); //mapper definition class receive_mapper: public m2_mapper<i_func_receiver, i_arch_receiver> { public: receive_mapper(sc_module_name name) : m2_mapper<i_func_receiver, i_arch_receiver>(name) {} void receive(void * data, unsigned long len){ out_port->receive(data, len, 1000);} }; //instantiation receive_mapper r_mapper("receive_mapper"); //mapping between ports M2_MAP(r, out_port, r_mapper, p, read_port); // setup physical time annotator std::vector<m2_event *> ptime_event_list; ptime_event_list.push_back(r.read_event_end); ptime_event_list.push_back(w.write_event_end); std::map<const char*, double, ltstr> ptime_table; ptime_table[r.read_event_end->get_full_name()]=1; ptime_table[w.write_event_end->get_full_name()]=2; m2_physical_time_annotator* ptime=new m2_physical_time_annotator("pt_annotator",ptime_event_list,&ptime_table); register_annotator(ptime); // setup logical time scheduler m2_logical_time_scheduler* ltime = new m2_logical_time_scheduler("lt_scheduler"); ltime->add_event(r.read_event_beg); ltime->add_event(r.read_event_end); ltime->add_event(w.write_event_beg); ltime->add_event(w.write_event_end); register_scheduler(ltime); Mapper FIGURE 10.7 Overview of M ETRO II design elements. Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 282 2009-10-2 282 Model-Based Design for Embedded Systems components via ports. There are two descriptions of component composi- tion: atomic components and composite components. An atomic component is a block specified in some language and is viewed by the framework as a black box with only its interface information exposed. A composite compo- nent is a group of one or more objects as well as any connections between them. When an existing IP is being imported, it will be encapsulated by a wrapper, which translates and exposes the appropriate events and inter- faces from the IP. The wrapped IP becomes an atomic component in the framework. 10.4.2.2 Ports Components can interface with each other via ports. Each port is character- ized by an interface that contains a set of methods. A method consists of a sequence of events, with a unique begin/end event pair. Variables in the scope of the begin event are method arguments. Variables in the scope of the end event are return values. By setting constraints between events associated with the ports of dif- ferent components, the execution of these components can be coordinated. There are two types of ports: required ports and provided ports. Required ports are used by components to request methods that are implemented in other components. Provided ports are used by components to provide meth- ods to other components. Connections between components are made only between a required port and a provided port with the same interface. The execution semantics that coordinate a pair of required and provided ports will be introduced in Section 10.4.3. 10.4.2.3 Constraint Solvers Constraints are used to specify the design via declarative means, as opposed to imperative specification which is contained in components. Constraints are described in terms of events: their status (enabled or disabled), their tags, and the values associated with them. The events referenced by constraints must be exposed by ports. Constraint solvers are objects that resolve these declaration constraints during runtime. Depending on the status, tags, and values of the events, con- straint solvers decide whether to enable or disable events, thereby coordinat- ing the execution of components. Designers can derive various constraint solvers from the base class solver provided by the M ETRO II infrastructure. The main function to be imple- mented is the one to resolve the constraints. In M ETRO II, a synchronization constraint solver is provided. Two events that are specified in a synchroniza- tion constraint need to be enabled at the same time—during simulation, they need to be enabled in the same iteration. Further examples will be given in Section 10.4.3. Synchronization constraints are used for mapping between the functionality and the architecture, as is explained later. Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 283 2009-10-2 Platform-Based Design and Frameworks: METROPOLIS and METRO II 283 10.4.2.4 Annotators and Schedulers In M ETROPOLIS, both the performance annotation and the scheduling of events were carried out by a type of special component called a quantity man- ager. As stated before, to have a more clear separation of design concerns, these two aspects will be handled separately by annotators and schedulers in M ETRO II. Annotators annotate events with quantities by writing tags. Each tag that represents some quantity (such as power and physical time) is determined in terms of the parameters supplied to the annotator, the status of the event, and the values of the event. Parameters are given by the designers based on the characterization of the architecture platforms. Only static parameters are permitted for annotators, which may not have their own state. For vari- ous quantities or quantities in various systems, designs can derive their own annotators from the annotator base class in M ETRO II. Currently, a physical time annotator is provided in the M ETRO II library. The instantiation of a physical time annotator is shown in Figure 10.7. The r.read_event_end and w.write_event_end are events associated with a reader and writer component, respectively. These two events are added to a list of events to be considered for annotation. In addition, a table indexed by these events is created along with the assigned time units required for execution (1 and 2 units, respectively). This list and the table are then added to the annotator object itself. If these events are present during the second phase of execution, their tags will be updated accordingly. Schedulers coordinate the execution of the components by enabling/dis- abling the events proposed by the processes of the components. Based on the local state of the scheduler, the status of the events, as well as their val- ues and tags, the scheduler determines the scheduling of the events. A base class scheduler is provided in M ETRO II for designers to derive various sched- ulers. A logical time scheduler that schedules the events based on the physi- cal time tags, and a round-robin scheduler that schedules the access to shared resources are provided as library schedulers. An example using the logical time scheduler is shown in the code snippet in Figure 10.7. 10.4.2.5 Mappers As a framework based on the PBD, M ETRO II supports mapping through map- pers, which synchronize the begin and end events of the functional meth- ods and architectural methods. Designers are only allowed to specify map- ping at this service level, with access to the parameters and return values of the methods. When the begin/end events in the functional and architectural methods are synchronized, the parameters and return values can be trans- fered between the two models. For instance, a functional method may have one parameter that the corresponding architectural method is unaware of. During mapping, the value of this parameter can be passed to the architec- tural method for its usage. M ETRO II provides an API to specify mappers at Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 284 2009-10-2 284 Model-Based Design for Embedded Systems the service level. The implementation of mappers is a synchronization con- straint solver with value passing of parameters and return values. An example of a mapper is shown in Figure 10.7. This mapper is called “receive_mapper” and is used to map the consumer in a producer–consumer design example to a processing element, p. During mapping when the receive method is called by the functional model with two arguments, the mapper’s out_port will call the architectural model’s receive method that has three arguments. Also shown in Figure 10.7 are the instantiation of the map- per along with how the mapper is connected between the functional model and the architectural model. 10.4.2.6 Adaptors There are various ways of handling heterogeneous MoCs in a design. One of the most common approaches is the hierarchical composition as in Ptolemy II [38]. With the hierarchical composition, each level of the hierarchy is homo- geneous, i.e., a single MoC exists at each level, while different interaction mechanisms are allowed to be specified at different levels in the hierarchy [26]. To allow models in two heterogeneous MoCs to communicate, a third MoC may need to be found within which the two will be embedded. In our experience, there is a strong need to interconnect heterogeneous models directly at the same level. For instance, the user may want to connect the output of a base-band-processing component (described by a dataflow model) to the input of an RF component (described by a continuous-time model). This way of handling complexity does not require changing the interface of a model in order to behave like another model. This is in line with one of our main concerns: being able to reuse IPs in different contexts. The complexity of this approach lies in designing the correct intercon- nections between different MoCs. To bridge the different semantics of het- erogeneous components, we use adaptors to modify events as they pass from one component to another. Denotationally, an adaptor is a relation, A ⊆ (V × T) × (V × T ), that maps events from one model to events of another model. Adaptors are connected with components through specialized adaptor channels. In the PBD methodology, adaptors can be regarded as the bridge between heterogeneous functional components or between heterogeneous architectural components. The M ETRO II infrastructure provides the base classes of adaptors and adaptor channels. M ETRO II also includes an exam- ple of adaptors between dataflow and finite-state machine (FSM) semantics. 10.4.3 METRO II Semantics Like METROPOLIS, the semantics of the METRO II framework will be cen- tered around the connection and coordination of components. The execu- tion semantics discussed here are involved in the simulation of a system for design-space exploration. Nicolescu/Model-Based Design for Embedded Systems 67842_C010 Finals Page 285 2009-10-2 Platform-Based Design and Frameworks: METROPOLIS and METRO II 285 10.4.3.1 Three-Phase Execution M ETRO II has three-phase execution semantics. In order to discuss this seman- tics, two other concepts must be introduced: process states and event states. In Figure 10.8, the states that an event can have are shown. Events can be inactive, proposed, and annotated. All events begin as inactive. As the self loop shows, they can remain inactive indefinitely. When a method call on a required port generates an event it becomes proposed. It will then be annotated. If the event is then deemed appropriate to enable (via a variety of scheduling decisions) it will transition to inactive again. Each process in METRO II has two states: running and suspended. Processes execute concurrently until an event is proposed on a required port of the component containing the process or until they are blocked on a provided port. At this point they transition to the suspended state. Once the event is enabled or the internal blocking is resolved, the processes return to the running state. Based on this treatment of events, the design is partitioned into three phases of execution. In the first phase, processes propose possible events; the second phase associates tags with the proposed events; and the third phase allows a subset of the proposed events to execute. 1. Base model execution. The base model consists of concurrently exe- cuting processes that may suspend only after proposing events or by 3b. Enable some events Phase 2Phase 1 FC FC AC 1. Block processes at interfaces 2. Annotate events Event enabled by CS Event disabled by CS and must be reannotated Event disabled by CS but keeps annotation Event proposed by processPropose event(s) or block Enable event or resume process M ETRO II process states Running Suspended Start M ETRO II event states Event annotated ProposedInactive Annotated AC Phase 3 Physical time Constraint solver 3a. Schedule resolution Resource scheduler Logical time FIGURE 10.8 M ETRO II three-phase execution semantics. . network selected for scheduling. Nicolescu /Model-Based Design for Embedded Systems 67842_C010 Finals Page 278 2009-10-2 278 Model-Based Design for Embedded Systems 10.4 METRO II Design Environment METRO. m2_logical_time_scheduler("lt_scheduler"); ltime->add_event(r.read_event_beg); ltime->add_event(r.read_event_end); ltime->add_event(w.write_event_beg); ltime->add_event(w.write_event_end); register_scheduler(ltime); Mapper FIGURE 10.7 Overview of M ETRO II design elements. Nicolescu /Model-Based Design for Embedded Systems 67842_C010 Finals Page 282 2009-10-2 282 Model-Based Design for Embedded Systems components via. method for its usage. M ETRO II provides an API to specify mappers at Nicolescu /Model-Based Design for Embedded Systems 67842_C010 Finals Page 284 2009-10-2 284 Model-Based Design for Embedded