Find and fix PS/PL performance-acceleration issues in your Zynq-based embedded system design using SDSoC’s emulation tools

2017年9月1日 | By News | Filed in: News.

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by Anthony Boorsma, DornerWorks

 

 

Why aren’t you getting the performance you expect after moving a task or tasks from the Zynq PS (processing system) to its PL (programmable logic)? If you used SDSoC to develop your embedded design, there’s help available. Here’s some advice from DornerWorks, a Premier Xilinx Alliance Program member. This blog is adapted from a recent post on the DornerWorks Web site titled “Fine Tune Your Heterogeneous Embedded System with Emulation Tools.

 

 

 

Thanks to Xilinx’s SDSoC Development Environment, offloading portions of your software algorithm to a Zynq SoC’s or Zynq UltraScale+ MPSoC’s PL (programmable logic) to meet system performance requirements is straightforward. Once you have familiarized yourself with SDSoC’s data-transfer options for moving data back and forth between the PS and PL, you can select the appropriate data mover that represents the best choice for your design. SDSoC’s software estimation tool then shows you the expected performance results.

 

Yet when performing the ultimate test of execution—on real silicon—the performance of your system sometimes fails to match expectations and you need to discover the cause… and the cure. Because you’ve offloaded software tasks to the PL, your existing software debugging/analysis methods do not fully apply because not all of the processing occurs in the PS.

 

You need to pinpoint the cause of the unexpected performance gap. Perhaps you made a sub-optimal choice of data mover. Perhaps the offloaded code was not a good candidate for offloading to the PL. You cannot cure the performance problem without knowing its cause.

 

Just how do you investigate and debug system performance on a Zynq-based heterogeneous embedded system with part of the code running in the PS and part in the PL?

 

If you are new to the world of debugging PL data processing, you may not be familiar with the options you have for viewing PL data flow. Fortunately, if you used SDSoC to accelerate software tasks by offloading them to the PL, there is an easy solution. SDSoC has an emulation capability for viewing the simulated operation of your PL hardware that uses the context of your overall system.

 

This emulation capability allows you to identify any timing issues with the data flow into or out of the auto-generated IP blocks that accelerate your offloaded software. The same capability can also show you if there is an unexpected slowdown in the offloaded software acceleration itself.

 

Using this tool can help you find performance bottlenecks. You can investigate these potential bottlenecks by watching your data flow through the hardware via the displayed emulation signal waveforms. Similarly, you can investigate the interface points by watching the data signals transfer data between the PS and the PL. This information provides key insights that help you find and fix your performance issues.

 

We’ll focus on the multiplier IP block from the Xilinx MMADD example to demonstrate how you can debug/emulate a hardware-accelerated function. For simplicity, we will focus on one IP block, the matrix multiplier IP block from the Multiply and Add example, shown in Figure 1.

 

 

 

Image1.jpg

 

Figure 1: Multiplier IP block with Port A expanded to show its signals

 

 

 

We will look at the waveforms for the signals to and from this Mmult IP block in the emulation. Specifically we will view the A_PORTA signals as shown in the figure above. These signals represent the data input for matrix A, which corresponds to the software input param A to the matrix multiplier function.

 

To get started with the emulation, enable generation of the “emulation model” configuration for the build in SDSoC’s project’s settings, as shown in Figure 2.

 

 

 

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Figure 2: The mmult Project Settings needed to enable emulation

 

 

 

Next, rebuild your project as normal. After building your project with emulation model support enabled in the configuration, run the emulator by selecting “Start/Stop Emulation” under the “Xilinx Tools” menu option. When a window opens, select “Start” to start the emulator. SDSoC will then automatically launch an instance of Xilinx Vivado, which triggers the auto-generated PL project that SDSoC created for you as a subproject within your SDSoC project.

 

We specifically want to view the A_PORTA signals of the Mmult IP block. These signals must be added to the Wave Window to be viewed during a simulation. The available Mmult signals can be viewed in the Objects pane by selecting the mmult_1 block in the Scopes pane. To add the A_PORTA signals to the Wave Window, select all of the “A_*” signals in the Objects pane, right click, and select “Add to Wave Window” as shown in Figure 3.

 

 

 

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Figure 3: Behavioral Simulation – mmult_1 signals highlighted

 

 

 

Now you can run the emulation and view the signal states in the waveform viewer. Start the emulator by clicking “Run All” from the “Run” drop-down menu as shown in Figure 4.

 

 

 

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Figure 4: Start emulation of the PL

 

 

 

Back SDSoC’s toolchain environment, you can now run a debugging session that connects to this emulation session as it would to your software running on the target. From the “Run” menu option, select “Debug As -> 1 Launch on Emulator (SDSoC Debugger)” to start the debug session as shown in Figure 5.

 

 

 

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Figure 5: Connect Debug Session to run the PL emulation

 

 

 

Now you can step or run through your application test code and view the signals of interest in the emulator. Shown below in Figure 6 are the A_PORTA signals we highlighted earlier and their signal values at the end of the PL logic operation using the Mmult and Add example test code.

 

 

Image6.jpg

 

Figure 6: Emulated mmult_1 signal waveforms

 

 

 

These signals tell us a lot about the performance of the offloaded code now running in the PL and we used familiar emulation tools to obtain this troubleshooting information. This powerful debugging method can help illuminate unexpected behavior in your hardware-accelerated C algorithm by allowing you to peer into the black box of PL processing, thus revealing data-flow behavior that could use some fine-tuning.

 

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September 1, 2017 at 02:41AM


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