Publications associées à Exact Synthesis of Majority-Inverter Graphs and Its Applications

Publications associées (31)

Scalable Logic Rewriting Using Don’t Cares

Giovanni De Micheli, Alessandro Tempia Calvino

Logic rewriting is a powerful optimization technique that replaces small sections of a Boolean network with better implementations. Typically, exact synthesis is used to compute optimum replacement on-the-fly, with possible support for Boolean don't cares. ...

2024

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Siang-Yun Lee

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

EPFL2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

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

Orthologic with Axioms

Viktor Kuncak, Simon Guilloud

We study the proof theory and algorithms for orthologic, a logical system based on ortholattices, which have shown practical relevance in simplification and normalization of verification conditions. Ortholattices weaken Boolean algebras while having polyno ...

Association for Computing Machinery2024

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Mohan Vamsi Nallapareddy, Pierre Vandergheynst, Felix Naef, Cédric Gobet, Francesco Craighero

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome densities, ...

PMLR2024

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

Equivariant Neural Architectures for Representing and Generating Graphs

Clément Arthur Yvon Vignac

Graph machine learning offers a powerful framework with natural applications in scientific fields such as chemistry, biology and material sciences. By representing data as a graph, we encode the prior knowledge that the data is composed of a set of entiti ...

EPFL2023

Results on Sparse Integer Programming and Geometric Independent Sets

Jana Tabea Cslovjecsek

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n. Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed ...

EPFL2023

Probabilistic methods for neural combinatorial optimization

Nikolaos Karalias

The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

EPFL2023

Utilizing XMG-based Synthesis to Preserve Self-Duality for RFET-Based Circuits

Giovanni De Micheli, Heinz Riener, Alessandro Tempia Calvino, Akash Kumar

Individual transistors based on emerging reconfigurable nanotechnologies exhibit electrical conduction for both types of charge carriers. These transistors (referred to as Reconfigurable Field-Effect Transistors (RFETs)) enable dynamic reconfiguration to d ...

2022

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

Logic Synthesis From Incomplete Specifications Using Disjoint Support Decomposition

Giovanni De Micheli, Andrea Costamagna

Approximate logic synthesis is an emerging field that tolerates errors in the synthesized logic circuits for better optimization quality. Indeed, in many computing problems, the requirement of preserving the exact functionality either results in unnecessar ...

IEEE2022

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

Motif Cut Sparsifiers

Mikhail Kapralov, Jakab Tardos, Mikhail Makarov

A motif is a frequently occurring subgraph of a given directed or undirected graph G (Milo et al.). Motifs capture higher order organizational structure of G beyond edge relationships, and, therefore, have found wide applications such as in graph clusterin ...

IEEE COMPUTER SOC2022

Graph Representation Learning with Optimal Transport: Analysis and Applications

Effrosyni Simou

In several machine learning settings, the data of interest are well described by graphs. Examples include data pertaining to transportation networks or social networks. Further, biological data, such as proteins or molecules, lend themselves well to graph- ...

EPFL2022

Preserving Self-Duality During Logic Synthesis for Emerging Reconfigurable Nanotechnologies

Giovanni De Micheli, Heinz Riener, Akash Kumar

Emerging reconfigurable nanotechnologies allow the implementation of self-dual functions with a fewer number of transistors as compared to traditional CMOS technologies. To achieve better area results for Reconfigurable Field-Effect Transistors (RFET)-base ...

IEEE2021

Three-Input Gates for Logic Synthesis

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

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

Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations

Mattia Atzeni

Text-based games (TBGs) have emerged as useful benchmarks for evaluating progress at the intersection of grounded language understanding and reinforcement learning (RL). Recent work has proposed the use of external knowledge to improve the efficiency of RL ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021