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. I serve in the program committees of AAAI (since 2024) and ICTAI (since 2025).

• 22-25 November 2025: We had a booth at the Science Festival 2025 to explain parallel computing to kids, teens and adults. [more info]
• 🎉8 November 2025: Really happy my paper "A GPU-based Constraint Programming Solver" has been accepted to AAAI 2026 with oral presentation.
• 3 November 2025: Welcome to Hakan Hasan who embarks with us on a PhD adventure!
• 11 September 2025: We organized the first parallel programming competition for MHPC students (with Paul and Wei). [more info]
• 2 July 2025: I presented my work on Turbo to the French conference JFPC. [more info]
• 20 June 2025: Team seminar #2 [slides: Yi-Nung, Hakan, Hedieh, Tobias, Pierre]
• 15 June 2025: Welcome to Wei Huang and Paul Aromolaran, students in the Master in HPC, joining the team this summer for an internship on parallel programming.
• 7 May 2025: During my 1-week stay at Zhejiang University (China) in the ZLAIRE laboratory, I gave a talk on abstract constraint programming on GPU [slides].
• 🎉2 May 2025: Our outreach activity "Supercomputer: Always Faster?" has been selected for the Science Festival 2025 in November (with Angelica Rings).
• 10 April 2025: I gave a talk at the IRILL (Center for Research and Innovation on Free Software) in Paris on constraint programming + GPU [slides][video (FR)].

All news 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.
• Our AAAI2026 paper describes the implementation of a GPU-based constraint solver within this model.
• FNR CORE Grant COMOC 2022-2025 to explore this strand of research (PI: P. Talbot, 384k€).

I have the pleasure to co-supervise and collaborate with several Master students, Ph.D. candidates and postdocs.

• Hasan Hakan, Ph.D. candidate, TBD, 2025-2028.
• Yi-Nung Tsao, Ph.D. candidate, Verification of Neural Networks by Abstract Interpretation, 2023-2027.
• Manuel Combarro, Ph.D. candidate, Multiobjective Constraint Programming, 2023-2026.
• Hedieh Haddad, Ph.D. candidate, Hyperparameter Optimization of Constraint Solver, 2023-2026.
• Tobias Fischbach, Ph.D. candidate, Optimization of Quantum Circuits, 2023-2026.
• Wei Huang, Master student, Improving Fixpoint Loop in Turbo (master thesis), March–August 2026.
• Anisa Meta, Master student, GPU-based Inprocessing in Turbo (master thesis), February–July 2026.

• Francesca Guffanti, postdoctoral researcher on the project COMOC, September 2024-March 2025.
• Thibault Falque, postdoctoral researcher on the project COMOC, January 2024-May 2025.
• Angelica Rings, Bachelor student, Outreach projects, 2024-2025.
• Paul Aromolaran, Master student, Adding Random Search in Turbo and help me to record videos on parallel computing, July-August 2025.