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Space Education Catalogue

Stage - Concevoir son architecture numérique sur FPGA

• Organisation : Sorbonne Université - Faculté des Sciences et Ingénierie
  (Sorbonne Université)
• Way of training : Life-long learning - short courses (advanced)
• Language(s): French
• Place: Sorbonne Université (French Regions: Ile-de-France)
• Prepared diploma/grade/title: Certificate of participation (Notification of training attendance/completion)
• 1st required level : French baccalauréat + 3

Course Details

Objectives : With their millions of reconfigurable gates, FPGA circuits provide access to very short execution times and allow the realization of complex functions and their updating during the lifetime of the product. They therefore play an important role in multiple fields such as sound and image processing, biomedical, data encryption and financial calculations for example. To ensure a good design of embedded digital electronics and to make the most of FPGA circuits, good expertise in hardware description languages ??(HDL) is necessary. It allows to synthesize but also to validate the functions to be carried out. At the end of this training, participants will be able to master hardware description using the standardized VHDL language and to implement a rigorous and systematic method to move from the specifications to the configured and validated digital system.

Public concerned : Technicians in charge of designing, developing or maintaining electronic cards based on FPGAs.
Engineers seeking to integrate FPGA components into their products (hardware acceleration, hardware security, etc.).

Prerequisites : Digital electronics: good knowledge of Boolean algebra and combinatorial and sequential logic functions.

Duration and terms : 21 h

Dedicated web site : https://fc.sorbonne-universite.fr/nos-offres/concevoir-son-architecture-numerique-sur-fpga/

Disciplines

• Engineering Sciences

Topics

• 8 - Electronics Systems : Analog and digital functions, Components, Microelectronics, Integrated Circuits, Samplers, ASIC/FPGA, Digital Signal Processors, Nanotechnologies
• 11 - Data Sciences: Applied Mathematics, Signal and Image Processing, Cryptography, Artificial Intelligence (machine learning, big data, etc.), Computer Science, Cloud, Software Engineering, Virtual Reality, Virtualization, Digital Twins, Metaverse, etc.