Heterogeneous Computing for Artificial Intelligence Applications

Explore how heterogeneous computing architectures combine CPUs and FPGAs to accelerate demanding artificial intelligence applications. This course introduces the principles behind CPU-FPGA systems, examining how different computing resources can be integrated and optimised to meet the performance, efficiency, and flexibility requirements of AI workloads. Participants will build a foundation in heterogeneous architectures and their role in developing high-performance AI solutions. 

What you will learn:

• Fundamentals of CPU-FPGA heterogeneous computing. 
• Architecture and characteristics of CPUs and FPGAs. 
• Principles of hardware-software co-design for AI applications. 
• Techniques for accelerating and optimising AI workloads. 
• Applications and benefits of heterogeneous computing for artificial intelligence. 

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