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FPGA computing systems: Background knowledge and introductory materials is an introductory training course on Digital Programmable Integrated Circuit (FPGA) computing systems published by Coursera Specialized Academy.
The use of different hardware components during the program execution process can have a significant effect on increasing the speed and improving the system performance and better responding to the needs of the client or the environment.
This adaptation can be implemented by the system designer and developer, and at the same time, it can be implemented in a prefabricated way in the component and the central processor. During the process of this training course, you will get to know FPGA technology and its implementation methods in a completely personalized way on desired platforms.
The main goal of this course is to teach reconfigurable computing systems designed based on FPGA technology. This technology is not used at all times, and it is up to the project manager or developers to determine when to use it and how to program and implement it.
What you will learn in the FPGA computing systems: Background knowledge and introductory materials training course:
- Digital programmable integrated circuit (FPGA) computing systems
- Different methods of implementing the adaptation capability of hardware components
- FPGA technology and its implementation methods are fully customized on desired platforms
- Reconfigurable computing systems
- And …
- Publisher: Coursera
- English language
- Duration: 46 hours
- Number of training weeks: 4
- Lecturer: Marco Domenico Santambrogio
- File format: mp4
- Course Level: Introductory
- Providing institution/university: Polytechnic University of Milan
FPGA computing systems course headings: Background knowledge and introductory materials:
A Bird’s Eye View on Adaptive Computing Systems
An introduction to Reconfigurable Computing
Reconfigurable Computing and FPGAs
Examples on how to configure an FPGA
An Introduction to Reconfigurations
Towards Partial Dynamic Reconfiguration and Complex FPGA-based systems
Closing remarks and future directions
FPGA computing systems Course images:
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