Improving the Asymmetric TSP by Considering Graph Structure

Recent works on cost based relaxations have improved Constraint Programming (CP) models for the Traveling Salesman Problem (TSP). We provide a short survey over solving asymmetric TSP with CP. Then, we suggest new implied propagators based on general graph properties. We experimentally show that such implied propagators bring robustness to pathological instances and highlight the fact that graph structure can significantly improve search heuristics behavior. Finally, we show that our approach outperforms current state of the art results.Comment: Technical repor

Modern techniques for constraint solving the CASPER experience

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaConstraint programming is a well known paradigm for addressing combinatorial problems which has enjoyed considerable success for solving many relevant industrial and academic problems. At the heart of constraint programming lies the constraint solver, a computer program which attempts to find a solution to the problem, i.e. an assignment of all the variables in the problemsuch that all the constraints are satisfied. This dissertation describes a set of techniques to be used in the implementation of a constraint solver. These techniques aim at making a constraint solver more extensible and efficient,two properties which are hard to integrate in general, and in particular within a constraint solver. Specifically, this dissertation addresses two major problems: generic incremental propagation and propagation of arbitrary decomposable constraints. For both problemswe present a set of techniques which are novel, correct, and directly concerned with extensibility and efficiency. All the material in this dissertation emerged from our work in designing and implementing a generic constraint solver. The CASPER (Constraint Solving Platformfor Engineering and Research)solver does not only act as a proof-of-concept for the presented techniques, but also served as the common test platform for the many discussed theoretical models. Besides the work related to the design and implementation of a constraint solver, this dissertation also presents the first successful application of the resulting platform for addressing an open research problem, namely finding good heuristics for efficiently directing search towards a solution

A Finite Domain Constraint Approach for Placement and Routing of Coarse-Grained Reconfigurable Architectures

Scheduling, placement, and routing are important steps in Very Large Scale Integration (VLSI) design. Researchers have developed numerous techniques to solve placement and routing problems. As the complexity of Application Specific Integrated Circuits (ASICs) increased over the past decades, so did the demand for improved place and route techniques. The primary objective of these place and route approaches has typically been wirelength minimization due to its impact on signal delay and design performance. With the advent of Field Programmable Gate Arrays (FPGAs), the same place and route techniques were applied to FPGA-based design. However, traditional place and route techniques may not work for Coarse-Grained Reconfigurable Architectures (CGRAs), which are reconfigurable devices offering wider path widths than FPGAs and more flexibility than ASICs, due to the differences in architecture and routing network. Further, the routing network of several types of CGRAs, including the Field Programmable Object Array (FPOA), has deterministic timing as compared to the routing fabric of most ASICs and FPGAs reported in the literature. This necessitates a fresh look at alternative approaches to place and route designs. This dissertation presents a finite domain constraint-based, delay-aware placement and routing methodology targeting an FPOA. The proposed methodology takes advantage of the deterministic routing network of CGRAs to perform a delay aware placement

GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP

Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale linearly with luminosity increase, compensated only partially by an increase of computing resources. The extension of fast simulation approaches to more use cases, covering a larger fraction of the simulation budget, is only part of the solution due to intrinsic precision limitations. The remainder corresponds to speeding-up the simulation software by several factors, which is out of reach using simple optimizations on the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport codes in order to make them benefit from fine-grained parallelism features such as vectorization, but also from increased code and data locality. This paper presents extensively the results and achievements of this R&D, as well as the conclusions and lessons learnt from the beta prototype.Comment: 34 pages, 26 figures, 24 table

Extension and evaluation of the global cardinality constraints functionality of the Gecode open source toolkit

Ο Προγραμματισμός με Περιορισμούς είναι μια μεθοδολογία της Τεχνητής Νοημοσύνης που αποσκοπεί να επιλύσει πραγματικά προβλήματα με αποτελεσματικό τρόπο. Σε αυ- τή την διπλωματική εργασία, επεκτείνουμε τον επιλυτή προβλημάτων ικανοποίησης περιορισμών ανοιχτού κώδικα Gecode, συνεισφέροντας στις δυνατότητές του σχετικά με Καθολικούς Περιορισμούς, συγκεκριμένα περιορισμούς Global Cardinality. Ένας Global Cardinality περιορισμός περιορίζει τον αριθμό εμφάνισης τιμών μέσα σε μια συλλογή μεταβλητών, ώστε να βρίσκεται μεταξύ συγκεκριμένων ορίων. Αναπτύσσουμε τον περιορισμό Global Cardinality With Costs, ο οποίος είναι παρόμοιος του Global Cardinality και επιπλέον συσχετίζει ένα κόστος με κάθε ανάθεση τιμής σε μεταβλητή, ενώ ταυτόχρονα απαιτεί το άθροισμα των κοστών να μην ξεπερνάει ένα όριο. Στη συνέχεια προσθέτουμε τον περιορισμό Symmetric Global Cardinality, ο οποίος ορίζεται πάνω σε μεταβλητές που αφορούν σύνολα, δίνοντας επιπλέον περιορισμούς γύρω από τον πληθικό αριθμό του κάθε συνόλου, πέραν των περιορισμών που αφορούν τις τιμές. Ερευνούμε τη βελτιστοποίηση της επίδοσής τους, πειραματιζόμενοι με διάφορες εναλλακτικές επιλογές υλοποίησης, και τελικά τους συγκρίνουμε ώστε να ανακαλύψουμε κάτω από ποιές συνθήκες είναι ωφέλιμοι, σε σχέση με την αποσύνθεσή τους σε περισσότερους απλούστερους περιορισμούς.Constraint Programming is an Artificial Intelligence methodology that aims to solve real world problems in an efficient way. In this work, we extend the open source constraint solver Gecode by expanding its features concerning Global Constraints, specifically Global Cardinality Constraints. A Global Cardinality Constraint restricts the value occurrences among a collection of variables, to be between certain bounds. We develop the Global Cardinality Constraint With Costs, which is similar to the Global Cardinality Constraint and additionally associates a cost with each variable-value assignment, while further restricting the sum of the costs related to the assigned variable-value pairs to not exceed a given cost bound. Moreover, we add the Symmetric Global Cardinality Constraint, which is defined on Set variables and introduces additional restrictions on the cardinality of each set, aside from the value occurrences. We attempt to optimize their performance by experimenting with various different implementation choices, and finally we evaluate our constraints to discover under which conditions they are beneficial compared to decomposing them to multiple simpler ones

Constraint programming on hierarchical multiprocessor systems

The work reported in this thesis is about constraint processing in the context of hierarchical multiprocessor systems, including distributed systems. More speci cally, it develops techniques and a system to help bringing the power available in today's multiprocessing networked systems into the constraint processing eld. Solving constraint speci ed problems is a process which lends itself naturally to parallelisation, as it usually implies going through very large search spaces, looking for a solution. Parallel constraint solving draws on the idea of dividing the search space among several workers, so the search may proceed faster, and thanks to the declarative nature of constraint programming, the parallelisation happens transparently as far as the user is concerned. However, to fully take advantage of the parallel computing power available, techniques must be developed to help ensure that the workers executing the search are kept busy at all times, which is an issue tackled by this work; RESUMO: Esta tese debruça-se sobre a programação por restrições no contexto dos sistemas multiprocessador hierárquicos, incluindo os sistemas distribuídos. Mais especificamente, o trabalho elaborado desenvolve as técnicas de resolução de problemas de satisfação de restrições recorrendo ao paralelismo. A actualidade do tema prende-se com a cada vez maior divulgação de que são objecto os sistemas multiprocessador que, juntamente com a omnipresença das redes de computadores, põe à nossa disposição uma capacidade de cálculo que necessita de ser posta a uso, o que tarda em acontecer. Nesta tese desenvolve-se um sistema que permite tirar partido desses recursos através do processamento de restrições A programação por restrições é um paradigma declarativo, em que o utilizador não tem de se preocupar com o controlo da computação, e a introdução de paralelismo nesta área pode realizar-se transparentemente. Por outro lado, o processo de pesquisa de soluções para problemas especificados por restrições adapta-se particularmente bem a ser paralelizado. Este tese apresenta uma abordagem _à resolução paralela de restrições, que junta paralelismo local, sob a forma de trabalhadores, com paralelismo distribuído, em que os actores são as equipas. O sistema construído, destinado a sistemas distribuídos de larga escala, que _é descrito e os seus resultados apresentados, inclui distribuição de trabalho, através de roubo de trabalho. Este funciona, localmente, sem a colaboração do roubado e, remotamente, com colaboração, num ambiente em que todas as equipas cooperam na procura da solução

Algorithms for the restricted linear coloring arrangement problem

The aim of this project is to develop efficient algorithms for solving or approximating the Minimum Restricted Linear Coloring Arrangement Problem. It is the first approach to its algorithms, and we will face the problem from different perspectives: constraint programming, backtracking, greedy, and genetic algorithms. As a second goal we are interested in providing theoretical results for particular graphs