Publications associées à Learning from survey propagation: a neural network for MAX-E-3-SAT

In Medio Stat Virtus: Combining Boolean and Pattern Matching

Giovanni De Micheli, Alessandro Tempia Calvino, Gianluca Radi

Technology mapping transforms a technology-independent representation into a technology-dependent one given a library of cells. This process is performed by means of local replacements that are extracted by matching sections of the subject graph to library ...

IEEE2024

Approximation Algorithms for Allocation and Network Design

Etienne Michel François Bamas

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

EPFL2023

Improving Standard-Cell Design Flow using Factored Form Optimization

Giovanni De Micheli, Alessandro Tempia Calvino

Factored form is a powerful multi-level representation of a Boolean function that readily translates into an implementation of the function in CMOS technology. In particular, the number of literals in a factored form correlates strongly with the number of ...

IEEE2023

NP Satisfiability for Arrays as Powers

Viktor Kuncak, Rodrigo Raya

We show that the satisfiability problem for the quantifier-free theory of product structures with the equicardinality relation is inNP. As an application, we extend the combinatory array logic fragmentto handle cardinality constraints. The resulting fragme ...

Springer, Cham2022

On Semi-Algebraic Proofs and Algorithms

Mika Tapani Göös

We give a new characterization of the Sherali-Adams proof system, showing that there is a degree-d Sherali-Adams refutation of an unsatisfiable CNF formula C if and only if there is an ε > 0 and a degree-d conical junta J such that viol_C(x) - ε = J, where ...

Schloss Dagstuhl - Leibniz-Zentrum für Informatik2022

A Majority Lemma for Randomised Query Complexity

Mika Tapani Göös, Gilbert Théodore Maystre

We show that computing the majority of n copies of a boolean function g has randomised query complexity R(Maj∘gⁿ) = Θ(n⋅R ̅_{1/n}(g)). In fact, we show that to obtain a similar result for any composed function f∘gⁿ, it suffices to prove a sufficiently stro ...

Schloss Dagstuhl - Leibniz-Zentrum für Informatik2021

Three-Input Gates for Logic Synthesis

Giovanni De Micheli, Mathias Soeken, Dewmini Sudara Marakkalage, Eleonora Testa, Heinz Riener

Most logic synthesis algorithms work on graph representations of logic functions with nodes associated with arbitrary logic expressions or simple logic functions and iteratively optimize such graphs. While recent multilevel logic synthesis efforts focused ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Logic Resynthesis of Majority-Based Circuits by Top-Down Decomposition

Giovanni De Micheli, Heinz Riener, Siang-Yun Lee

Logic resynthesis is the problem of finding a dependency function to re-express a given Boolean function in terms of a given set of divisor functions. In this paper, we study logic resynthesis of majority-based circuits, which is motivated by the increasin ...

IEEE2021

From Boolean functions to quantum circuits: A scalable quantum compilation flow in C++

Giovanni De Micheli, Fereshte Mozafari Ghoraba, Heinz Riener, Giulia Meuli, Bruno Schmitt Antunes

We propose a flow for automated quantum compila- tion. Our flow takes a Boolean function implemented in Python as input and translates it into a format appropriate for reversible logic synthesis. We focus on two quantum compilation tasks: uniform state pre ...

2021

Boolean satisfiability in quantum compilation

Giovanni De Micheli, Mathias Soeken, Fereshte Mozafari Ghoraba, Heinz Riener, Giulia Meuli, Bruno Schmitt Antunes

Quantum compilation is the task of translating a quantum algorithm implemented in a high-level quantum programming language into a technology-dependent instructions flow for a physical quantum computer. To tackle the large gap between the quantum program a ...

ROYAL SOC2020