Welcome!

This is the website of Pierre Talbot. I'm a research scientist at the University of Luxembourg. I'm working on new theories of constraint reasoning and parallel programming. I'm also the co-director of the Master in High Performance Computing.

• 9 January 2025: I gave a talk at the LERIA @University of Angers on constraint programming + GPU [slides].
• 6-10 January 2025: I visit the University of Angers in the context of a collaboration with Éric Monfroy on the table global constraint.
• 28-30 November 2024: We had a booth at the Researchers' Days to explain parallel computing to kids, teens and adults :)
• 🎉22-30 October 2024: We were selected to participate in the Poland Open Hackathon in collaboration with mentors from Nvidia to optimize Turbo! More about our adventure and results here.
• 1 October 2024: Welcome to Angelica Rings, Bachelor student, who joins us to develop a video game for the Researcher's Days in the context of the project COMOC.
• 15 September 2024: Welcome to Francesca Guffanti, Ph.D. in mathematics, who joins us for a postdoc to strengthen the mathematical foundation of our parallel model of computation in the project COMOC.
• 🎉9 September 2024: Hedieh Haddad got her paper Selecting Search Strategy in Constraint Solvers using Bayesian Optimization accepted to ICTAI-24 [more info].
• 🎉10 July 2024: Hedieh Haddad got her paper Comparison of Hyperparameter Optimization Methods for Selecting Search Strategy of Constraint Programming Solvers accepted to PTHG-24 [more info].
• 17 June 2024: We organize the new Abstract Interpretation Workshop 2024, feel free to join :-)
• 26 April 2024: Our proposal with Angelica Rings A Musical Game to Understand the Challenge of Collaboration in Computing for the Researchers' Days (28-30 November 2024) has been accepted.
• 23 April 2024: I gave a seminar to the parallel and combinatorial optimization group (PCOG) on an introduction to abstract interpretation, slides.

Can abstract interpretation be the backbone theory to unify constraint reasoning approaches?

• Goal I: Combine constraint solvers (by reduced products) to more efficiently solve combinatorial problems.
• Goal II: Generalize reasoning procedures (e.g., propagation, multiobjective algorithms, clause learning) to monotone functions working over any abstract domains.

We are working on a new theory of combinatorial optimization called abstract satisfaction, first introduced by D'Silva, Haller and Kroening. It relies on lattice theory and abstract interpretation to unify the subfields of combinatorial optimization.

Highlights:

• The lattice land project is a collection of C++ libraries implementing abstract domains such as intervals, octagons and new ones such as propagator completion.
• Our TPLP journal paper (2020) introduces the propagator completion and new a product of abstract domains.

Can lattice theory be the backbone of a safe model of parallel programming?

• Goal I: Make parallel programs correct-by-construction.
• Goal II: Take advantage of specialized hardware (e.g., GPUs, FPGAs, quantum architectures)

The foundation of this language is the same than for abstract constraint reasoning: lattice theory. In short: data are lattices, programs are monotone functions and the execution is the computation of a fixpoint. Our primary focus and application is to accelerate the algorithms developed for abstract constraint reasoning on parallel architectures.

Highlights:

• Turbo is an abstract constraint solver fully executing on the GPU.
• cuda-battery provides C++ data structures working on both the CPU and GPU (CUDA).
• Our AAAI2022 paper describes the foundation of this parallel model of computation.
• FNR CORE Grant COMOC 2022-2025 to explore this strand of research (PI: P. Talbot, 384k€).

I have the pleasure to co-supervise and work with several Ph.D. students and postdocs.

• Thibault Falque, postdoctoral researcher on the project COMOC, 2024-2025.
• Francesca Guffanti, postdoctoral researcher on the project COMOC, 2024-2025.
• Hedieh Haddad, Ph.D. candidate, Hyperparameter Optimization of Constraint Solver, 2023-2025.
• Manuel Combarro, Ph.D. candidate, Multiobjective Constraint Programming, 2023-2025.
• Yi-Nung Tsao, Ph.D. candidate, Verification of Neural Networks by Abstract Interpretation, 2023-2026.
• Tobias Fischerbach, Ph.D. candidate, Optimization of Quantum Circuits, 2023-2026.
• Angelica Rings, Bachelor student, A Musical Game to Understand the Challenge of Collaboration in Computing, 2024.