Constraint propagation in Mozart

This thesis presents constraint propagation in Mozart which is based on computational agents called propagators. The thesis designs, implements, and evaluates propagator-based propagation engines. A propagation engine is split up in generic propagation services and domain specific domain solvers which are connected by a constraint programming interface. Propagators use filters to perform constraint propagation. The interface isolates filters from propagators such that they can be shared among various systems. This thesis presents the design and implementation of a finite integer set domainsolver for Mozart which reasons over bound and cardinality approximations of sets.The solver cooperates with a finite domain solver to improve its propagation and expressiveness. This thesis promotes constraints to first-class citizens and thus, provides extra control over constraints. Novel programming techniques taking advantage of the first-class status of constraints are developed and illustrated.Diese Dissertation beschreibt Constraint-Propagierung in Mozart, die auf Berechnungsagenten, Propagierer genannt, basiert. Die Dissertation entwirft, implementiert und evaluiert Propagierer-basierte Propagierungsmaschinen. Eine Propagierungsmaschine ist aufgeteilt in generische Propagierungsdienste und domänenspezifische Domänenlöser, die durch eine Schnittstelle zur Constraint-Programmierung miteinander verbunden sind. Propagierer benutzen Filter, um Constraints zu propagieren. Die Schnittstelle isoliert Filter von Propagierern, so dass Programmkodes von Filtern von verschiedenen Systemen genutzt werden können. Diese Dissertation präsentiert den Entwurf und die Implementierung eines Domänenlösers über endliche Mengen von ganzen Zahlen für Mozart, die über Mengen- und Kardinalitätsschranken approximiert werden. Dieser kooperiert mit einem Löser über endlichen Bereichen, um die Propagierung und die Ausdrucksfähigkeit zu verbessern. Diese Dissertation erhebt Constraints zu emanzipierten Datenstrukturen und stellt auf dieseWeise zusätzliche Steuerungsmöglichkeiten über Constraints zur Verfügung. Des Weiteren werden neuartige Programmiertechniken für emanzipierte Constraints entwickelt und demonstriert

Constraint propagation in Mozart

This thesis presents constraint propagation in Mozart which is based on computational agents called propagators. The thesis designs, implements, and evaluates propagator-based propagation engines. A propagation engine is split up in generic propagation services and domain specific domain solvers which are connected by a constraint programming interface. Propagators use filters to perform constraint propagation. The interface isolates filters from propagators such that they can be shared among various systems. This thesis presents the design and implementation of a finite integer set domainsolver for Mozart which reasons over bound and cardinality approximations of sets.The solver cooperates with a finite domain solver to improve its propagation and expressiveness. This thesis promotes constraints to first-class citizens and thus, provides extra control over constraints. Novel programming techniques taking advantage of the first-class status of constraints are developed and illustrated.Diese Dissertation beschreibt Constraint-Propagierung in Mozart, die auf Berechnungsagenten, Propagierer genannt, basiert. Die Dissertation entwirft, implementiert und evaluiert Propagierer-basierte Propagierungsmaschinen. Eine Propagierungsmaschine ist aufgeteilt in generische Propagierungsdienste und domänenspezifische Domänenlöser, die durch eine Schnittstelle zur Constraint-Programmierung miteinander verbunden sind. Propagierer benutzen Filter, um Constraints zu propagieren. Die Schnittstelle isoliert Filter von Propagierern, so dass Programmkodes von Filtern von verschiedenen Systemen genutzt werden können. Diese Dissertation präsentiert den Entwurf und die Implementierung eines Domänenlösers über endliche Mengen von ganzen Zahlen für Mozart, die über Mengen- und Kardinalitätsschranken approximiert werden. Dieser kooperiert mit einem Löser über endlichen Bereichen, um die Propagierung und die Ausdrucksfähigkeit zu verbessern. Diese Dissertation erhebt Constraints zu emanzipierten Datenstrukturen und stellt auf dieseWeise zusätzliche Steuerungsmöglichkeiten über Constraints zur Verfügung. Des Weiteren werden neuartige Programmiertechniken für emanzipierte Constraints entwickelt und demonstriert

A Variant of Concurrent Constraint Programming on GPU

The number of cores on graphical computing units (GPUs) is reaching thousands nowadays, whereas the clock speed of processors stagnates. Unfortunately, constraint programming solvers do not take advantage yet of GPU parallelism. One reason is that constraint solvers were primarily designed within the mental frame of sequential computation. To solve this issue, we take a step back and contribute to a simple, intrinsically parallel, lock-free and formally correct programming language based on concurrent constraint programming. We then re-examine parallel constraint solving on GPUs within this formalism, and develop Turbo, a simple constraint solver entirely programmed on GPUs. Turbo validates the correctness of our approach and compares positively to a parallel CPU-based solver

SecDec-3.0: numerical evaluation of multi-scale integrals beyond one loop

SecDec is a program which can be used for the factorization of dimensionally regulated poles from parametric integrals, in particular multi-loop integrals, and the subsequent numerical evaluation of the finite coefficients. Here we present version 3.0 of the program, which has major improvements compared to version 2: it is faster, contains new decomposition strategies, an improved user interface and various other new features which extend the range of applicability.Comment: 46 pages, version to appear in Comput.Phys.Com

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

SAT and CP: Parallelisation and Applications

This thesis is considered with the parallelisation of solvers which search for either an arbitrary, or an optimum, solution to a problem stated in some formal way. We discuss the parallelisation of two solvers, and their application in three chapters.In the first chapter, we consider SAT, the decision problem of propositional logic, and algorithms for showing the satisfiability or unsatisfiability of propositional formulas. We sketch some proof-theoretic foundations which are related to the strength of different algorithmic approaches. Furthermore, we discuss details of the implementations of SAT solvers, and show how to improve upon existing sequential solvers. Lastly, we discuss the parallelisation of these solvers with a focus on clause exchange, the communication of intermediate results within a parallel solver. The second chapter is concerned with Contraint Programing (CP) with learning. Contrary to classical Constraint Programming techniques, this incorporates learning mechanisms as they are used in the field of SAT solving. We present results from parallelising CHUFFED, a learning CP solver. As this is both a kind of CP and SAT solver, it is not clear which parallelisation approaches work best here. In the final chapter, we will discuss Sorting networks, which are data oblivious sorting algorithms, i. e., the comparisons they perform do not depend on the input data. Their independence of the input data lends them to parallel implementation. We consider the question how many parallel sorting steps are needed to sort some inputs, and present both lower and upper bounds for several cases

Model-based symbolic design space exploration at the electronic system level: a systematic approach

In this thesis, a novel, fully systematic approach is proposed that addresses the automated design space exploration at the electronic system level. The problem is formulated as multi-objective optimization problem and is encoded symbolically using Answer Set Programming (ASP). Several specialized solvers are tightly coupled as background theories with the foreground ASP solver under the ASP modulo Theories (ASPmT) paradigm. By utilizing the ASPmT paradigm, the search is executed entirely systematically and the disparate synthesis steps can be coupled to explore the search space effectively.In dieser Arbeit wird ein vollständig systematischer Ansatz präsentiert, der sich mit der Entwurfsraumexploration auf der elektronischen Systemebene befasst. Das Problem wird als multikriterielles Optimierungsproblem formuliert und symbolisch mit Hilfe von Answer Set Programming (ASP) kodiert. Spezialisierte Solver sind im Rahmen des ASP modulo Theories (ASPmT) Paradigmas als Hintergrundtheorien eng mit dem ASP Solver gekoppelt. Durch die Verwendung von ASPmT wird die Suche systematisch ausgeführt und die individuellen Schritte können gekoppelt werden, um den Suchraum effektiv zu durchsuchen