Pré-publication, Document de travail
ParSys
Parallel Systems- ParSys
Research Themes
The team’s activity also involves the use of state-of-the-art parallel architectures to achieve optimal performance of codes developed for future exascale platforms. In addition, drawing inspiration from natural, efficient and robust phenomena, the team studies natural distributed algorithms to design efficient solutions for emerging networks, and even to develop robust distributed circuits in bacterial cell consortia, for computational or medical purposes (biological computers, smart drugs, etc.).
The main challenges concerning the algorithms studied in the ParSys team are: performance optimization, scaling and load balancing, fault tolerance and energy saving.
The applications (ranging from scientific computing, quantum computing and data analysis to network protocols and microbiological circuits) meet essential industrial or scientific needs and are the subject of industrial cooperation with ATOS-Bull, Total, and EdF, among others.
Coordination
Last publications
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Thèse
Matthieu Robeyns. Mixed precision algorithms for low-rank matrix and tensor approximations. Computer Science [cs]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG095⟩. ⟨tel-04885863⟩
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Communication dans un congrès
Brice Chichereau, Stéphane Vialle, Patrick Carribault. Fully integrated quantum method for classical register allocation in LLVM. WIHPQC 2024 – International Workshop on Integrating High-Performance and Quantum Computing and QXE24 – IEEE Quantum Week 2024, Sep 2024, Montréal, Canada. ⟨hal-04839424⟩
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Communication dans un congrès
Julien Rauch, Brice Chichereau, Stéphane Vialle, Patrick Carribault, Damien Rontani. Investigating parallel execution of quantum Machine Learning circuits on superconducting hardware. QSET 2024 – 4th International Workshop on Quantum Software Engineering and Technology IEEE Quantum Week 2024 (QCE’24), Sep 2024, Montréal, Canada. ⟨hal-04812905⟩
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Proceedings/Recueil des communications
Hugo Gabrielidis, Filippo Gatti, Stephane Vialle. Pipeline for Semantic Segmentation of Large Railway Point Clouds. Intelligent Data Engineering and Automated Learning – IDEAL 2024, Lecture Notes in Computer Science, 15346, Springer Nature Switzerland, pp.167-179, 2025, Lecture Notes in Computer Science, ⟨10.1007/978-3-031-77731-8_16⟩. ⟨hal-04811058⟩
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Communication dans un congrès
Pierre Fraigniaud, Minh Hang Nguyen, AmiArchitectures et modèles pour l'Interaction Paz. Brief Announcement: Agreement Tasks in Fault-Prone Synchronous Networks of Arbitrary Structures. DISC 2024, 2024, Madrid, Spain. ⟨10.4230/LIPIcs.DISC.2024.47⟩. ⟨hal-04799395⟩
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Communication dans un congrès
Hagit Attiya, Pierre Fraigniaud, AmiArchitectures et modèles pour l'Interaction Paz, Sergio Rajsbaum. Brief Announcement: Solvability of Three-Process General Tasks. DISC 2024, 2024, Madrid, Spain. ⟨10.4230/LIPIcs.DISC.2024.42⟩. ⟨hal-04799398⟩
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Communication dans un congrès
Leyla Biabani, AmiArchitectures et modèles pour l'Interaction Paz. k-Center Clustering in Distributed Models. SIROCCO 2024, May 2024, Vietri sul Mare, Italy. pp.83-100, ⟨10.1007/978-3-031-60603-8_5⟩. ⟨hal-04799381⟩
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Article dans une revue
Pierre Fraigniaud, AmiArchitectures et modèles pour l'Interaction Paz. The topology of local computing in networks. Journal of Applied and Computational Topology, 2024, 8 (4), pp.1069-1098. ⟨10.1007/s41468-024-00185-6⟩. ⟨hal-04799384⟩
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Article dans une revue
AmiArchitectures et modèles pour l'Interaction Paz, Hugo Rincon Galeana, Stefan Schmid, Ulrich Schmid, Kyrill Winkler. The Time Complexity of Consensus Under Oblivious Message Adversaries. Algorithmica, 2024, 86 (6), pp.1830-1861. ⟨10.1007/s00453-024-01209-4⟩. ⟨hal-04799403⟩