Developing AI Inference Solutions with the Vitis AI Platform
Course Description
This course describes how to use the Vitis™ AI development platform in conjunction with DNN algorithms, models, inference and training, and frameworks on cloud and edge computing platforms The emphasis of this course is on:
- Illustrating the Vitis AI tool flow
- Utilizing the architectural features of the Deep Learning Processor Unit (DPU)
- Optimizing a model using the AI quantizer and AI compiler
- Utilizing the Vitis AI Library to optimize pre-processing and post-processing functions Creating a custom platform and application
- Deploying a design
- Providing an overview of the AMD Xilinx Kria™ K26 SOM and its advantages
Release Date
May 2022.
Level
AI 3
Who Should Attend?
Software and hardware developers, AI/ML engineers, data scientists, and anyone who needs to accelerate their software applications using AMD Xilinx devicesPrerequisites
- Basic knowledge of machine learning concepts
- Neural Networks Explained - Learning Tutorial for Beginners: www.youtube.com/watch?v=GvQwE2OhL8I
- How Convolutional Neural Networks Work: www.youtube.com/watch?v=FmpDIaiMIeA
- Deep learning frameworks (such as TensorFlow, PyTorch, and Caffe)
- Comfort with the C/C++/Python programming language
- Software development flowBasic knowledge of machine learning conceptsv
Skills Gained
After completing this comprehensive training, you will have the necessary skills to:- Illustrating the Vitis AI tool flow
- Utilizing the architectural features of the Deep Learning Processor Unit (DPU)
- Optimizing a model using the AI quantizer and AI compiler
- Utilizing the Vitis AI Library to optimize pre-processing and post-processing functions
- Creating a custom platform and application
- Deploying a design
- Providing an overview of the AMD Xilinx Kria K26SOM and its advantages
Course Outline
- Introduction to the Vitis AI Development Environment
- Frameworks Supported by the Vitis AI Development Environment
- Setting Up the Vitis AI Development Environment
- Overview of ML Concepts
- AI Optimizer
- AI Quantizer and AI Compiler
- AI Profiler
- Introduction to the Deep Learning Processor Unit (DPU)
- DPUCZDX8G Architecture Training Overview – Zynq Devices
- Vitis AI Library
- Creating a Custom Hardware Platform with the DPU Using the Vivado Design Suite Flow - Edge
- Creating a DPU Kernel Using the Vitis Environment Flow - Edge
- Creating a Vitis Embedded Acceleration Platform
- Creating a Custom Application (Edge)
- AMD Xilinx Kria KV260 Vision AI Starter Kit Overview
- Customizing the AI Models
- Developing AI Inference Solutions with the Vitis AI Platform Quiz
Event Schedule
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