• Design Continuum for Next Generation Energy-Efficient Compute Nodes
  • ANR Project
  • Oct 2015 to Apr 2019
  • Partners: LIRMM and Cortus SAS
  • The CONTINUUM project aims to address the energy-efficiency challenge in future computing systems by investigating a design continuum for compute nodes, which seamlessly goes from software to technology levels via hardware architecture. Power saving opportunities exist at each of these levels, but the real measurable gains will come from the synergistic focus on all these levels as considered in this project. Then, a cross-disciplinary collaboration is promoted between computer science and microelectronics, to achieve two main breakthroughs: i) combination of state-of-the-art heterogeneous adaptive embedded multicore architectures with emerging communication and memory technologies and, ii) power-aware dynamic compilation techniques that suitably match such a platform.


  • Secure Codes to thwart Cyber-physical Attacks
  • ANR CHIST-ERA Project
  • Jan 2016 to Dec 2018
  • Partners: Télécom ParisTech, Paris 8, Université Catholique de Louvain, Sabancı University
  • In the SECODE project, we specify and design error correction codes suitable for an efficient protection of sensitive information in the context of Internet of Things (IoT) and connected objects. Such codes mitigate passive attacks, like memory disclosure, and active attacks, like stack smashing. The innovation of this project is to leverage these codes for protecting against both cyber and physical attacks. The main advantage is a 360° coverage of attacks of the connected embedded systems, which is considered as a smart connected device and also a physical device. The outcome of the project is first a method to generate and execute cyber-resilient software, and second to protect data and its manipulation from physical threats like side-channel attacks. Theses results are demonstrated by using a smart sensor application with hardened embedded firmware and tamper-proof hardware platform.


  • AutoTuning and Adaptivity appRoach for Energy efficient eXascale HPC systems
  • European project – H2020 FET HPC
  • Sep 2015 to Aug 2018
  • Partners: Politecnico di Milano, ETH Zürich, Universidade do Porto, CINECA, IT4Innovations, Dompé Farmaceutici Spa, Sygic a.s.
  • The main goal of the ANTAREX project is to provide a breakthrough approach to map, runtime manage and autotune applications for green and heterogeneous High Performance Computing systems up to the Exascale level. One key innovation of the proposed approach consists of introducing a separation of concerns (where self-adaptivity and energy efficient strategies are specified aside to application functionalities) promoted by the definition of a Domain Specific Language (DSL) inspired by aspect-oriented programming concepts for heterogeneous systems. The new DSL will be introduced for expressing the adaptivity/energy/performance strategies and to enforce at runtime application autotuning and resource and power management. The goal is to support the parallelism, scalability and adaptability of a dynamic workload by exploiting the full system capabilities (including energy management) for emerging large-scale and extreme-scale systems, while reducing the Total Cost of Ownership (TCO) for companies and public organizations.


  • WCET-Aware Parallelization of Model-Based Applications for Heterogeneous Parallel Systems
  • European project – H2020 RIA
  • Jan 2016 to Dec 2018
  • Partners: Karlsruher Institut fuer Technologie (KIT), SCILAB enterprises SAS, Recore Systems BV, Université de Rennes 1, Technologiko Ekpaideftiko Idryma (TEI) Dytikis Elladas, Absint GmbH, Deutsches Zentrum fuer Luft und Raumfahrt EV, Fraunhofer
  • Increasing performance and reducing cost, while maintaining safety levels and programmability are the key demands for embedded and cyber-physical systems in European domains, e.g. aerospace, automation, and automotive. For many applications, the necessary performance with low energy consumption can only be provided by customized computing platforms based on heterogeneous many-core architectures. However, their parallel programming with time-critical embedded applications suffers from a complex toolchain and programming process. The ARGO research project will address this challenge with a holistic approach for programming heterogeneous multi- and many-core architectures using automatic parallelization of model-based real-time applications. ARGO will enhance WCET-aware automatic parallelization by a cross-layer programming approach combining automatic tool-based and user-guided parallelization to reduce the need for expertise in programming parallel heterogeneous architectures. The ARGO approach will be assessed and demonstrated by prototyping comprehensive time-critical applications from both aerospace and industrial automation domains on customized heterogeneous many-core platforms.

Nano2017 PSAIC

  • Performance and Size Auto-tuning through Iterative Compilation
  • National funding – Programme de recherche & développement coopératif
  • Sep 2014 to Dec 2017
  • Partners: STMicroelectronics, Inria teams CAMUS, CORSE, AriC
  • The PSAIC (Performance and Size Auto-tuning through Iterative Compilation) project concerns the automation of program optimization through the combination of several tools and techniques such as: compiler optimization, profiling, trace analysis, iterative optimization and binary analysis/rewriting. For any given application, the objective is to devise through a fully automated process a compiler profile optimized for performance and code size. For this purpose, we are developing instrumentation techniques that can be focused and specialized to a specific part of the application aimed to be monitored. PACAP contributes program analyses at the binary level, as well as binary transformations. We will also study the synergy between static (compiler-level) and dynamic (run-time) analyses.


  • Calcul Parallèle pour Applications Critiques en Temps et Sûreté – Parallel computations for safety-critical real-time applications
  • National funding – projet “Investissement d’avenir”
  • Oct 2014 to Feb 2018
  • Partners: Kalray (lead), Airbus, Open-Wide, Safran Sagem, IS2T, Real Time at Work, Dassault Aviation, Eurocopter, MBDA, Supersonic Imagine, ProbaYes, IRIT, Onera, Verimag, Inria, Irisa, Tima and Armines
  • The project objective is to develop a hardware and software platform based on manycore architectures, and to demonstrate the relevance of these manycore architectures (and more specifically the Kalray manycore) for several industrial applications. The Kalray MPPA manycore architecture is currently the only one able to meet the needs of embedded systems simultaneously requiring high performance, lower power consumption, and the ability to meet the requirements of critical systems (low latency I/O, deterministic processing times, and dependability).

We are proud participants of :

Former projects


  • WCET: SEmantics, Precision and Traceability
  • ANR project, grant ANR-12-INSE-0001
  • Oct 2012 to Dec 2016
  • Partners: Verimag, IRIT, Continental
  • W-SEPT is a collaborative research project focusing on worst-case execution time guarantees. The main goal is to improve the precision and the traceability of semantics information through the compilation flow, from high-level description (such as the Lustre synchronous language) down to C and binary levels. It is supported by the competitiveness clusters (pôles de compétitivité) Aerospace Valley and Minalogic.

Inria Project Lab Multicore

  • Large scale virtualization for performance scaling and portability
  • Inria Project Lab
  • 2013 to 2016
  • Partners: Inria teams ALGORILLE, CAMUS, REGAL, RUNTIME, as well as DALI.
  • Multicore processors are becoming the norm in most computing systems. However supporting them in an efficient way is still a scientific challenge. This large-scale initiative introduces a novel approach based on virtualization and dynamicity, in order to mask hardware heterogeneity, and to let performance scale with the number and nature of cores. It aims to build collaborative virtualization mechanisms that achieve essential tasks related to parallel execution and data management. We want to unify the analysis and transformation processes of programs and accompanying data into one unique virtual machine. We hope delivering a solution for compute-intensive applications running on general-purpose standard computers.

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