Model-Based Design for Embedded Systems- P71 ppsx

Nicolescu/Model-Based Design for Embedded Systems 67842_C020 Finals Page 686 2009-10-2 686 Model-Based Design for Embedded Systems rst Clock&Reset 1 0 MM M X X01234 01 01 03 03 03 03 03 03 56789ABCDEF 977 250 μm XX XX XX XX Now 8000000 pa XXX 0 0 0 0 00 00 00 00 0 0 0 00 00 00 00 1 clk Configuration control D valid iond en clk_gel pattern sel Input from Fiber/circuits Output from Fiber/circuits input_0 input_1 input_2 input_3 output_0 output_1 output_2 output_3 Clock & Reset FIGURE 20.28 FIG test system block diagram: Areas in the digital domain are executed in ModelSim while areas in the analog and optical domains are executed in Chatoyant. CLk4X CLk4X Data1 PIN PD array Receiver circuitry 8:1 DDR deserializer 1:8 DDR Serializer 1:8 DDR Serializer 8:1 DDR deserializer Dout (7:0) Dout (15:8) Clk1X_Out RXTX Driver circuitry 4 free-space optical links Electrical output Electrical input Din (7:0) Din (15:8) Clk1X_IN Clk4X_IN VCSEL array Data2 FIGURE 20.29 SPOT system block diagram showing the digital data entering in parallel to the UTSI transceiver chip, serialized transmitted over free-space optics, deserialized with clock-recovery, back into parallel data. (Courtesy of [52].) propagated light back into analog signals at which point the analog circuits amplify and feed the de-serializing logic in the digital domain. Figure 20.29 shows the system block diagram. Nicolescu/Model-Based Design for Embedded Systems 67842_C020 Finals Page 687 2009-10-2 CAD Tools for Multi-Domain Systems on Chips 687 SPOT tests the ability of the co-simulation environment to work with a global clock signal. This clock signal, generated by the digital domain, is transmitted with the data, and thus crosses the co-simulation interface. This means that there are a large number of periodic events occurring. This illustrates the simulation behavior of a synchronous system versus an asyn- chronous system in the co-simulation environment. Given these two systems, we next show the results of runtimes and event traffic for different time resolutions of the SYNC_PULSE parameter. A total of four resolutions were tested, 1 ps, 10 ps, 100 ps, and 1 ns. These values were chosen since the systems run at relatively high frequencies, in the range of nanoseconds for both data bit rate and clock speed. All simulations were performed on a Dual 1.70 MHz Intel Xeon Processor Dell Precision with 3 GBs of RAM running Red Hat Linux 7.3, kernel version 2.4.18-3SMP. 20.3.2.3 FIG Runtimes The following set of charts show the runtime and event traffic seen in each of the resolution steps. Figure 20.30 shows the runtime, in seconds versus the four different time resolutions. Figure 20.31 shows the event counts seen from the Chatoyant and ModelSim perspectives. As seen in Figure 20.30, the runtimes decreased as the resolution became coarser. One thing to note is the logarithmic-like decay. This is most likely because of the total simulation time of the experiment rather than the time resolution. Since all simulations were performed for a simulation time of 154.22 141.01163.75214.43 100 ps 1 ns10 ps1 ps 0.00 50.00 100.00 150.00 200.00 250.00 Series1 Seconds Runtime vs. sync resolution FIGURE 20.30 Runtime versus Sync resolution for FIG. Nicolescu/Model-Based Design for Embedded Systems 67842_C020 Finals Page 688 2009-10-2 688 Model-Based Design for Embedded Systems Chatoyant RX 0 1000 2000 3000 4000 5000 Number of events vs. resolution Event count Chatoyant TX ModelSim RX ModelSim TX 4 1 ps Sync 1,077 4,307 12 4 10 ps Sync 37 147 12 4 100 ps Sync 8 32 12 4 1 ns Sync 4 16 12 FIGURE 20.31 Number of events per simulation for FIG. 1.4 us, the closer the granularity of the resolution is to the magnitude of the end time, the smaller the difference will be in runtimes. This is explained by the notion that less event processing is performed since more events are ignored between synchronization points. Therefore, event processing over- head is reduced. Also, the amount of event traffic decreases by two orders of magnitude between 1 ps and 1 ns resolutions. This is also related to the fact that more events are processed at higher resolutions. 20.3.2.4 SPOT Runtimes The SPOT system yields a different perspective on the co-simulation system. Figure 20.32 shows the runtime results versus resolution and Figure 20.33 shows the event traffic at each resolution. As seen in Figure 20.32, the runtimes do decrease, in general, with respect to an increasing granularity. The exception to this is the 10 ps resolution, which shows a slight increase in runtime compared to the 1 ps resolution. This may be because of the processing of more event changes given the peri- odicity of the clock signal in the system. Regardless of this outlier, there is still a general trend for decreasing runtimes as well as decreased event traf- fic with lower resolutions. SPOT having a higher runtime versus FIG indicates the effect of the clock signal on performance. Since there is a clock having a consistent event Nicolescu/Model-Based Design for Embedded Systems 67842_C020 Finals Page 689 2009-10-2 CAD Tools for Multi-Domain Systems on Chips 689 Seconds 0.00 200.00 400.00 600.00 800.00 1000.00 1200.00 1400.00 1600.00 1800.00 2000.00 Runtime vs. sync resolution 1 ps 10 ps 100 ps 1 ns 1605.67 1722.50 843.31 842.65 FIGURE 20.32 Runtime results versus resolution granularity. change at a fixed frequency, the number of events per synchronization cycle increases. This is seen by the higher event counts in each SPOT simulation versus those for FIG. This amount, spread uniformly across the entire simu- lation in SPOT, versus FIG which has dense cluster of events separated by a large time gap, exemplifies the overhead associated with processing events. 20.4 Summary In summary, we have presented a co-simulation environment for mixed- domain, mixed-signal simulation that spans the realms of HDL digital logic, analog electrical, optical, and mechanical systems. A variety of modeling techniques are used to develop analog component models that are evalu- ated using continuous time models. These component behaviors commu- nicate via specific ports that pass complex messages between components. Those messages, and the corresponding execution of the component mod- els, are coordinated by a DE simulation backbone. This backbone, built on Ptolemy, also runs in coordination with a commercial HDL simulator. Nicolescu/Model-Based Design for Embedded Systems 67842_C020 Finals Page 690 2009-10-2 690 Model-Based Design for Embedded Systems 4000 3500 3000 2500 2000 1500 1000 500 0 1 ps Sync 146 Chatoyant RX Chatoyant TX ModelSim RX ModelSim TX 146 146 142 175 175 144 3499 3499 1750 179435433543 150 150 150 10 ps Sync 100 ps Sync 1 ns Sync Number of events vs. resolution Event count FIGURE 20.33 Event traffic versus resolution granularity. This system, known as Chatoyant–ModelSim Co-Simulation Environment, provides an interface between the multi-domain analog realm handled by Chatoyant and the digital realm, handled by ModelSim. As seen in the co-simulation experiments, there are a few factors that affect runtime performance. Asynchronous systems with more clustering of events within certain windows generally have a better runtime than syn- chronous systems that have a steady load of events. Also, as predicted, the resolution of synchronization, defined in the context of the PDES conserva- tive approach and implemented using Unix IPC, has an effect on runtime performance by reducing the event processing overhead, at the cost of accu- racy. This cost is assessed based on the system and requirements a particular user has for the simulation. 20.4.1 Conclusions Multi-domain modeling and multi-rate simulation tools are required to sup- port mixed-technology system design. This chapter has shown Chatoyant’s support for simulating and analyzing optical MEM systems with models for optical, electrical, and mechanical models for components and signals. By supporting a variety of component and signal modeling techniques and multiple abstraction levels, Chatoyant has the ability to perform and ana- lyze mixed-signal tradeoffs, which makes it valuable to multi-technology system designers. 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Nicolescu /Model-Based Design for Embedded Systems 67842_C020 Finals Page 688 2009-10-2 688 Model-Based Design for Embedded Systems Chatoyant RX 0 1000 2000 3000 4000 5000 Number. Nicolescu /Model-Based Design for Embedded Systems 67842_C020 Finals Page 686 2009-10-2 686 Model-Based Design for Embedded Systems rst Clock&Reset 1 0 MM. with a commercial HDL simulator. Nicolescu /Model-Based Design for Embedded Systems 67842_C020 Finals Page 690 2009-10-2 690 Model-Based Design for Embedded Systems 4000 3500 3000 2500 2000 1500 1000 500 0 1