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Space Education Catalogue

Stage - Système de haut niveau (HLS) pour system on chip

• Organisations :
  • CY Cergy Paris Université
    (CY Cergy Paris Université)
  • 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 + 5

Course Details

Objectives : Providing hardware acceleration, system security and product scalability, FPGA circuits are now an essential component of embedded electronic devices. To meet the ever-shorter cycles of products placed on the market, it is becoming essential to master its relative complexity through the expert use of (new) high-level description tools (High-level synthesis, or HLS). At the end of this training, participants will be able to master the entire design flow of a complex digital system using an HLS language.

Public concerned : Engineers responsible for designing, developing or maintaining systems on chip based on FPGAs.

Prerequisites : Digital electronics: FPGA and hardware description language (VHDL, Verilog, etc.).
Microprocessor: architecture and low-level programming language (C language).
The “System on Chip (SoC): co-design of software and hardware embedded on FPGA” course is an excellent entry point for this training.
Computer science: algorithms is a second possible entry point for this training.

Duration and terms : 21 h

Dedicated web site : https://fc.sorbonne-universite.fr/nos-offres/synthese-de-haut-niveau-hls-pour-system-on-chip/

Disciplines

• Engineering Sciences

Topics

• 7 - Embedded/Cyberphysical Systems: Embedded Networks, Real Time Systems, Formal Methods, Embedded Software, Avionics, Instrumentation...
• 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.