Designing with Versal AI Engine: Kernel Programming and Optimization Online

Software and hardware developers, system architects, and anyone who needs to accelerate their software applications using AMD devices

• Comfort with the C/C++ programming language
• Software development flow
• Experience using Vitis software for application acceleration development flow
• Designing with Versal AI Engines course

Vitis unified software platform

After completing this training, you will have the necessary skills to:

• Utilize various Versal AI Engine kernel optimization techniques, such as compiler directives, software pipelining, coding for performance, and core utilization
• Apply C coding guidelines for performance improvement, including function inlining, pointer restricting, and code shuffling
• Identify and debug the various problems that arise in application development
• Implement an AI Engine kernel using AI Engine APIs for a symmetric FIR with aie::sliding_mul_sym_xy_ops
• Implement an AI Engine kernel using a non-symmetric FIR with aie::sliding_mul_sym_xy_ops
• Debug an application using the simulation debugging methodology and event traces

• AI Engine Architecture

  Introduces the architecture of the AI Engine and describes the AI Engine interfaces that are available, including the memory, lock, core debug, cascaded stream, and AXI-Stream interfaces. {Lecture}

• Versal AI Engine Data Movement and Interfaces

  Describes the memory module architecture for the AI Engine and how memory can be accessed by the AI Engines in the AI Engine arrays. Also reviews the AI Engine array interfaces. {Lecture}

• Overview of AI Engine Kernel Optimization

  Explains the various AI Engine kernel optimization techniques, such as compiler directives, software pipelining, coding for performance, and core utilization. {Lecture}

• AI Engine Kernel Optimization – Compiler Directives

  Describes the usage of compiler directives for loop unrolling, loop flattening, and software pipelining to help improve the performance of AI Engine kernels. {Lecture}

• AI Engine Kernel Optimization – Coding Style

  Covers the C coding guidelines for performance improvement, including function inlining, pointer restricting, and code shuffling. Also covers calculating AI Engine utilization for the kernels to help improve performance. The lab illustrates applying kernel optimization techniques such as the restrict keyword, custom pragmas, and code restructuring. {Lecture, Lab}

• Advanced C++ Kernel Programming

  Provides an overview of C++ kernel template functionality and the different types of states and kernel instance states using C++ classes. Also covered are kernel instance states with scalar parameters in a constructor as well as kernel instance states with array parameters in a constructor. {Lecture, Lab}

• Vector Data Types (Review)

  Provides an AI Engine functional overview and identifies the supported vector data types and high-width registers for allowing single instruction, multiple data (SIMD) instructions. {Lecture}

• AI Engine Symmetric and Asymmetric Filter Implementation

  Describes AI Engine APIs for symmetric and asymmetric FIR implementation, such as aie::sliding_mul_sym_xy_ops operators. Also, provides an overview of the DSP library, which can help with creating filters more easily and faster. {Lecture, Lab}

• Debugging AI Engine Applications 1

  Describes the application simulation debugging methodology as well as debugging with event traces, such as AI Engine events, DMA events, lock events, and stream events. Also demonstrates how to visualize these events in the Vitis unified software platform. {Lecture}

• Debugging AI Engine Applications 2 (Use Cases)

  Reviews various use cases of problems that arise, such as memory conflicts and deadlock analysis. Also covers performance analysis (profiling) in hardware. {Lecture, Lab}

• Versal AI Engine DSP Library Overview [Optional]

  Provides an overview of the available DSP library, which enables faster development and comes with ready-to-use example designs that help with using the library and tools. {Lecture, Labs}