This example simulates a monostatic radar system. It uses dataflow domain in Simulink® to automatically partition the data-driven portions of the radar system into multiple threads and thereby improving the performance of the simulation by executing it on your desktop's multiple cores.
The dataflow execution domain allows you to make use of multiple cores in the simulation of computationally intensive systems. This example shows how dataflow as the execution domain of a subsystem improves simulation performance of the model. To learn more about dataflow and how to run Simulink models using multiple threads, see Multicore Execution using Dataflow Domain (DSP System Toolbox).
This example simulates a simple end-to-end monostatic radar. Rectangular pulses are amplified by the transmitter block then propagated to and from a target in free-space. Noise and amplification are then applied in the receiver preamp block to the return signal, followed by a matched filter. Range losses are compensated for and the pulses are noncoherently integrated.
This example uses dataflow domain in Simulink to make use of multiple cores on your desktop to improve simulation performance. The Domain parameter of the Dataflow Subsystem in this model is set as Dataflow. You can view this by selecting the subsystem and then selecting View>Property Inspector. Dataflow domains automatically partition your model and simulate the system using multiple threads for better simulation performance. Once you set the Domain parameter to Dataflow, you can use Dataflow Simulation Assistant to analyze your model to get better performance. You can open the Dataflow Simulation Assistant, by clicking on the Dataflow assistant button below the Automatic frame size calculation parameter in Property Inspector.
In the Dataflow Simulation Assistant, click the Analyze button to start the analysis of the dataflow domain for simulation performance. Once the analysis is finished, the Dataflow Simulation Assistant shows how many threads the dataflow subsystem will use during simulation.
After analyzing the model, the assistant shows one thread because the data dependency between the blocks in the model prevents blocks from being executed concurrently. By pipelining the data dependent blocks, the Dataflow Subsystem can increase concurrency for higher data throughput. Dataflow Simulation Assistant shows the recommended number of pipeline delays as Suggested Latency. The suggested latency value is computed to give the best performance.
The following diagram shows the Dataflow Simulation Assistant where the Dataflow Subsystem currently specifies a latency value of zero, and the suggested latency for the system is four.
Click the Accept button next to Suggested Latency in the Dataflow Simulation Assistant to use the recommended latency for the Dataflow Subsystem.
Dataflow Simulation Assistant now shows the number of threads as four meaning that the blocks inside the dataflow subsystem simulate in parallel using four threads. Use of four pipeline delays increased the number of blocks that can be run in parallel inside Dataflow Subsystem. Latency value can also be entered directly in the Property Inspector for "Latency" parameter. Simulink shows the latency parameter value using tags at the output ports of the dataflow subsystem.
We measure the performance improvement of using dataflow domain by comparing the execution time taken for running the model with and without using dataflow. Execution time is measured using the sim command, which returns the simulation execution time of the model. These numbers and analysis were published on a Windows desktop computer with Intel® Xeon® CPU E5-1650 v3 @ 3.5 GHz 6 Cores 12 Threads processor.
Simulation execution time for multithreaded model = 18.05s Simulation execution time for single-threaded model = 23.91s Actual speedup with dataflow: 1.3x
This example shows how dataflow execution domain can improve performance in simulation of a radar system by using multiple cores on the desktop.