This example shows how an audio beamforming system simulation model in Simulink® can have improved performance using dataflow domain. It uses the dataflow domain in Simulink to automatically partition the data-driven portions of the communications 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.
This example shows acoustic beamforming using a uniform linear array (ULA) of microphones. The model simulates the reception of three audio signals from different directions on a 10-element uniformly spaced linear microphone array. After the addition of thermal noise at the receiver, beamforming is applied for different source angles and the result is played on a sound device. The audio source that needs to be played in the audio player can be selected using the dialog from the Select Source block.
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.
The Dataflow Simulation Assistant suggests changing model settings for optimal simulation performance. To accept the proposed model settings, next to Suggested model settings for simulation performance, click Accept all. Alternatively, you can expand the section to change the settings individually. In this example the model settings are already optimal. 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 three threads. This is because the three beamformer blocks are computationally intensive and can run in parallel. The three beamformer blocks however, depend on the Microphone Array and the Receiver blocks. Pipeline delays can be used to break this dependency and increase concurrency. The 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 one. Click the Accept button next to Suggested Latency in the Dataflow Simulation Assistant to use the recommended latency for the 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 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 W-2133 @ 3.6 GHz 6 Cores 12 Threads processor.
Simulation execution time for multithreaded model = 4.03s Simulation execution time for single-threaded model = 6.26s Actual speedup with dataflow: 1.6x
This example shows how multithreading using dataflow domain can improve performance in a monostatic radar system simulation model using multiple cores on the desktop.