34th International Workshop on Rapid System Prototyping (RSP)

Workshop Webpage


Please visit the RSP website https://conferences.imt-atlantique.fr/rsp-symposium for more details.

About


The International Workshop on Rapid System Prototyping (RSP) emphasizes design experience sharing and collaborative approach between hardware and software research communities from industry and academy. It considers prototyping as an iterative design approach for embedded hardware and software systems. The RSP series of workshop aim at bridging the gaps in embedded system design between applications, architectures, tools, and technologies to achieve rapid system prototyping of emerging software and hardware systems.

Organizers


Prof. Frederic Rousseau
Univ. Grenoble Alpes, France

Prof. Fabiano Hessel
PUCRS, Brazil

Prof. Amer Baghdadi
IMT Atlantique/Lab-STICC, France

Prof. Kenneth Kent
University of New Brunswick, Canada

Prof. Sungjoo Yoo
Seoul National University

Program Schedule


Indicated time is in CET (Europe) time zone

9:00 am – Welcome and Opening Remarks

9:05 am – 10:00 am  Keynote – Session Chair: Kenneth Kent, University of New Brunswick

  • Prof. Frédéric Pétrot, TIMA Lab/University Grenoble-Alpes, Digital Hardware Acceleration for Neural Networks: Implementation Considerations

10:00 am – 10:30 am  Coffee break

10:30 am – 12:00 pm  Session 1

  • Choonghoon Park, Hyunsu Moh, Jimin Lee, Changjae Yi and Soonhoi Ha
    Fast and Accurate Virtual Prototyping of an NPU with Analytical Memory Modeling
  • Navid Jafarof and Kenneth Kent
    The Impact of Heterogeneous Logic on Adders and Multipliers in VTR
  • Mohamed Nadeem, Jan Kleinekathöfer and Rolf Drechsler
    Polynomial Formal Verification exploiting Constant Cutwidth

12:00 pm – 1:30 pm    Lunch break

1:30 pm – 3:00 pm  Session 2

  • Felipe Gohring de Magalhães, Mahdi Nikdast and Gabriela Nicolescu
    SerIOS: Enhancing Hardware Security in Integrated Optoelectronic Systems
  • Alireza Azadi, Amir Amir Arjomand and Kenneth Kent
    Extending Memory Compatibility with Yosys Front-End in VTR Flow
  • Tobias Strauch
    MRPHS: A Verilog RTL to C++ Model Compiler Using Intermediate Representations for Object-oriented, Model-driven Prototyping
  • Raphaële Milan, Loic Lagadec, Théotime Bollengier, Lilian Bossuet and Ciprian Teodorov
    Integrating Quick Resource Estimators in Hardware Construction Framework for Design Space Exploration

3:00 pm – 3:30 pm    Coffee break

3:30 pm – 5:00 pm  Session 3

  • Henrique Amaral Misson, Rim Zrelli, Maroua Ben Attia, Felipe Gohring de Magalhães and Gabriela Nicolescu
    RaDaML: A Modeling Language for DO-178C High-Level Requirements in Airspace Systems
  • Colin Stéphenne, Felipe Göhring de Magalhães, Frédéric Cuppens, Gabriela Nicolescu and Jean-Yves Ouattara
    Security assessment of a commercial router using physical access: a case study
  • Melih Peker and Ozcan Ozturk
    Fast Compiler Optimization Flag Selection
  • Fearghal Morgan
    HDLGen and ChatGPT Case Study: RISC-V Processor VHDL and Verilog Model, Testbench and EDA Project Capture

5:00 pm  – End of Workshop

Keynote – Digital Hardware Acceleration for Neural Networks: Implementation Considerations

Frédéric Pétrot, Professor at TIMA Lab, Grenoble Institute of Technology, University Grenoble-Alpes, France

Abstract: The computations performed to achieve inference with deep neural networks range from hundreds of MFLOPs to tens of GFLOPs, and require access to a number of parameters that goes from around a million to over billions. Under these conditions, conventional CPUs have shown their limits, and programmable hardware architectures with a high level of parallelism have been developed. The silicon surface area and energy consumption of these solutions is very high, and a great deal of work is done to find more economical solutions, by playing on multiple factors. This keynote will first give an overview of the approaches currently being pursued to improve performance and power consumption, while minimizing the loss of precision, and second focus on the specific example of a ternary neural network designed and developed in our group.

Bio: Frédéric Pétrot received the PhD degree in Computer Science from Universite Pierre et Marie Curie (Paris VI), Paris, France, in 1994, where has been Assistant Professor in Computer Science until September 2004. He joined TIMA in September 2004, where he holds a professor position at Grenoble Institute of Technology, France. His research interests are in multiprocessor systems on chip architectures, including circuits and software aspects, and CAD tools for the design and evaluation of hardware/software systems. He currently holds the Digital Hardware AI Architectures chair of Grenoble Multidisciplinary Institute in Artificial Intelligence.