Explore Different Implementations of the Sobel Filter: Hand-Coded vs. Vitis Vision Library

In this section, we will focus on implementing an optimized hand-coded version of the Sobel operator in HLS and comparing its performance with the Sobel operator from the Vitis Vision Library. The first challenge we will encounter is the installation and configuration of the Vitis Vision Library, with all installation details provided in this document. Next, we will deploy the different versions of the Sobel HLS kernel onto the board and test the hardware acceleration performance within the PYNQ framework. A comparison of different implementations of the Sobel operator shows that using the Vitis Vision Library is more than three times faster than the Hand-Coded Sobel acceleration kernel when run on the same device and interface. Therefore, we need to master not only the design process and optimization techniques for HLS kernels but also learn to implement suitable operators using the existing Vitis Acceleration library.

Comparison

The advantages and disadvantages of the two methods are as follows:

Method	Advantages	Disadvantages
Hand-Coded Sobel	Highly customizable	Time-consuming to develop and optimize
	Potential for tailored optimization for specific needs	Requires deep knowledge of HLS and algorithm intricacies
Vitis Vision Library	Faster development time	Less flexibility in customization
	Pre-optimized for performance	Dependent on library updates
	Easier to implement

Content

Part	Topic	Description	Environment
1	Software Implementation	Software Implementation with OpenCV-Python Library	Jupyter Notebook
2	HLS Kernel Programming	Hand-Coded Sobel HLS Kernel to Extract Image edges	AMD Vitis HLS 2023.2
2	HLS Kernel Programming	Using Sobel in Vitis Vision Library to Extract Image Edges	AMD Vitis HLS 2023.2
3	System-level Integration	Create the kernel Graph and the test bench	Jupyter Notebook
		Load the overlay and run the application on the PYNQ framework
		Visualize the results and analyze the performance

Installation and Deployment Steps

Hand-Coded Version:
- Follow the Sobel GUI flow tutorial or the tcl flow steps to generate the PYNQ overlay.
- Deploy both the hand-written HLS Sobel kernel and the Vitis Vision Library Sobel kernel onto the board.
- Ensure that the PYNQ framework is correctly set up to support hardware acceleration.
- Test the performance of both implementations within the PYNQ framework.
- Measure metrics such as execution time, resource utilization, and power consumption.
Vitis Vision Library Version :
- Detailed instructions for installing the Vitis Vision Library.
  - If you are using Windows system, please refer to this guide.
  - If you are using Linux system, please refer to this guide.
- Ensure all dependencies and environment settings are configured correctly.
- Follow the configuration steps to set up the library within your development environment.