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Documents authored by Michel, Laurent

Document
DOI: 10.4230/LIPIcs.CP.2024.28
CP for Bin Packing with Multi-Core and GPUs

Authors: Fabio Tardivo, Laurent Michel, and Enrico Pontelli

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
The BinPacking constraint models the requirements of many logistics, resource allocation, and production scheduling applications. This paper explores new avenues based on the impressive computational power of modern GPUs to propagate the BinPacking constraint. This work showcases how the perspective of massive parallelization can lead to novel approaches, such as the use of a portfolio of lower bounds, to enhance the pruning of the BinPacking constraints. It delivers insights into the design choices and challenges presented by GPU platform for constraint propagation. The paper evaluates a GPU-accelerated propagator against both sequential and parallel CPU versions, as well as state-of-the-art approaches. Comparisons across various benchmarks from the literature show strong performances with respect to both CPU versions and the standard pruning approach. When compared to techniques based on Linear Programming, our approach proves valuable for large instances or when spending extensive time to obtain the best possible bound is not convenient.
Cite as

Fabio Tardivo, Laurent Michel, and Enrico Pontelli. CP for Bin Packing with Multi-Core and GPUs. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 28:1-28:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{tardivo_et_al:LIPIcs.CP.2024.28,
  author =	{Tardivo, Fabio and Michel, Laurent and Pontelli, Enrico},
  title =	{{CP for Bin Packing with Multi-Core and GPUs}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{28:1--28:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.28},
  URN =		{urn:nbn:de:0030-drops-207138},
  doi =		{10.4230/LIPIcs.CP.2024.28},
  annote =	{Keywords: Constraint Propagation, Bin Packing, Parallelism, GPU, Lower Bounds}
}
Document
DOI: 10.4230/LIPIcs.CP.2022.17
DUELMIPs: Optimizing SDN Functionality and Security

Authors: Timothy Curry, Gabriel De Pace, Benjamin Fuller, Laurent Michel, and Yan (Lindsay) Sun

Published in: LIPIcs, Volume 235, 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)

Abstract
Software defined networks (SDNs) define a programmable network fabric that can be reconfigured to respect global networks properties. Securing against adversaries who try to exploit the network is an objective that conflicts with providing functionality. This paper proposes a two-stage mixed-integer programming framework. The first stage automates routing decisions for the flows to be carried by the network while maximizing readability and ease of use for network engineers. The second stage is meant to quickly respond to security breaches to automatically decide on network counter-measures to block the detected adversary. Both stages are computationally challenging and the security stage leverages large neighborhood search to quickly deliver effective response strategies. The approach is evaluated on synthetic networks of various sizes and shown to be effective for both its functional and security objectives.
Cite as

Timothy Curry, Gabriel De Pace, Benjamin Fuller, Laurent Michel, and Yan (Lindsay) Sun. DUELMIPs: Optimizing SDN Functionality and Security. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 17:1-17:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{curry_et_al:LIPIcs.CP.2022.17,
  author =	{Curry, Timothy and De Pace, Gabriel and Fuller, Benjamin and Michel, Laurent and Sun, Yan (Lindsay)},
  title =	{{DUELMIPs: Optimizing SDN Functionality and Security}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{17:1--17:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.17},
  URN =		{urn:nbn:de:0030-drops-166468},
  doi =		{10.4230/LIPIcs.CP.2022.17},
  annote =	{Keywords: Network security, mixed integer programming, large neighborhood search}
}
Document
DOI: 10.4230/LIPIcs.CP.2022.24
Heuristics for MDD Propagation in HADDOCK

Authors: Rebecca Gentzel, Laurent Michel, and Willem-Jan van Hoeve

Published in: LIPIcs, Volume 235, 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)

Abstract
Haddock, introduced in [R. Gentzel et al., 2020], is a declarative language and architecture for the specification and the implementation of multi-valued decision diagrams. It relies on a labeled transition system to specify and compose individual constraints into a propagator with filtering capabilities that automatically deliver the expected level of filtering. Yet, the operational potency of the filtering algorithms strongly correlate with heuristics for carrying out refinements of the diagrams. This paper considers how to empower Haddock users with the ability to unobtrusively specify various such heuristics and derive the computational benefits of exerting fine-grained control over the refinement process.
Cite as

Rebecca Gentzel, Laurent Michel, and Willem-Jan van Hoeve. Heuristics for MDD Propagation in HADDOCK. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 24:1-24:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{gentzel_et_al:LIPIcs.CP.2022.24,
  author =	{Gentzel, Rebecca and Michel, Laurent and van Hoeve, Willem-Jan},
  title =	{{Heuristics for MDD Propagation in HADDOCK}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{24:1--24:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.24},
  URN =		{urn:nbn:de:0030-drops-166534},
  doi =		{10.4230/LIPIcs.CP.2022.24},
  annote =	{Keywords: Decision Diagrams}
}
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