Matthieu Moy
Grenoble Institute of Technology
43 Papers
343 Citations
Matthieu Moy is an academic researcher from Grenoble Institute of Technology. The author has contributed to research in topics: SystemC & Transaction-level modeling. The author has an hindex of 17, co-authored 41 publications. Previous affiliations of Matthieu Moy include STMicroelectronics & Centre national de la recherche scientifique.
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Papers
Pinapa: an extraction tool for SystemC descriptions of systems-on-a-chip
Matthieu Moy,Florence Maraninchi,Laurent Maillet-Contoz +2 more
- 18 Sep 2005
TL;DR: Pinapa is a tool to extract both architecture and behavior information from SystemC code, with very few limitations, and can be used as a front-end for various analysis tools, ranging from "superlint" to model-checking.
LusSy: An open tool for the analysis of systems-on-a-chip at the transaction level
TL;DR: The tool is able to extract information from SystemC code, and to build a set of parallel automata that capture the semantics of a SystemC design, including the transaction-level specific constructs, which provides the first executable formal semantics of SystemC.
System-level modeling of energy in TLM for early validation of power and thermal management
Tayeb Bouhadiba,Matthieu Moy,Florence Maraninchi +2 more
- 18 Mar 2013
TL;DR: This paper addresses the instrumentation of a timed transaction-level model of the hardware with information on the power consumption of the individual components that can cope not only with power-state models, but also with Joule-per-bit traffic models, and avoids simulation artifacts when used in a functional/power/temperature co-simulation.
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Parallel programming with SystemC for loosely timed models: a non-intrusive approach
Matthieu Moy
- 18 Mar 2013
TL;DR: This work proposes an approach that explicitly targets loosely timed systems, and offers the user a set of primitives to express tasks with duration, as opposed to the notion of time in SystemC which allows only instantaneous computations and time elapses without computation.
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•Posted Content
Succinct Representations for Abstract Interpretation
TL;DR: This work improves previously proposed techniques for guided static analysis and the generation of disjunctive invariants by combining them with techniques for succinct representations of paths and symbolic representations for transitions based on static single assignment.