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The implementation of new programming languages benefits from interpretation because it is simple, flexible and portable. The only downside is speed of execution, as there remains a large performance gap between even efficient interpreters and systems that include a just-in-time (JIT) compiler. Augmenting an interpreter with a JIT, however, is not a small task. Today, Java JITs are typically method-based. To compile whole methods, the JIT must re-implement much functionality already provided by the interpreter, leading to a ``big bang'' development effort before the JIT can be deployed. Adding a JIT to an interpreter would be easier if we could more gradually shift from dispatching virtual instructions bodies implemented for the interpreter to running instructions compiled into native code by the JIT. We show that virtual instructions implemented as lightweight callable routines can form the basis for a very efficient interpreter. Our new technique, interpreted traces, identifies hot paths, or traces, as a virtual program is interpreted. By exploiting the way traces predict branch destinations our technique markedly reduces branch mispredictions caused by dispatch. Interpreted traces are a high-performance technique, running about 25% faster than direct threading. We show that interpreted traces are a good starting point for a trace-based JIT. We extend our interpreter so traces may contain a mixture of compiled code for some virtual instructions and calls to virtual instruction bodies for others. By compiling about 50 integer and object virtual instructions to machine code we improve performance by about 30% over interpreted traces, running about twice as fast as the direct threaded system with which we started.

The implementation of new programming languages benefits from interpretation because it is simple, flexible and portable. The only downside is speed of execution, as there remains a large performance gap between even efficient interpreters and systems that include a just-in-time (JIT) compiler. Augmenting an interpreter with a JIT, however, is not a small task. Today, Java JITs are typically method-based. To compile whole methods, the JIT must re-implement much functionality already provided by the interpreter, leading to a ``big bang'' development effort before the JIT can be deployed. Adding a JIT to an interpreter would be easier if we could more gradually shift from dispatching virtual instructions bodies implemented for the interpreter to running instructions compiled into native code by the JIT. We show that virtual instructions implemented as lightweight callable routines can form the basis for a very efficient interpreter. Our new technique, interpreted traces, identifies hot paths, or traces, as a virtual program is interpreted. By exploiting the way traces predict branch destinations our technique markedly reduces branch mispredictions caused by dispatch. Interpreted traces are a high-performance technique, running about 25% faster than direct threading. We show that interpreted traces are a good starting point for a trace-based JIT. We extend our interpreter so traces may contain a mixture of compiled code for some virtual instructions and calls to virtual instruction bodies for others. By compiling about 50 integer and object virtual instructions to machine code we improve performance by about 30% over interpreted traces, running about twice as fast as the direct threaded system with which we started.

NP-hard problems of higher-dimensional orthogonal packing are considered. We look closer at their logical structure and show that they can be decomposed into problems of a smaller dimension with a special contiguous structure. This decomposition influences the modeling of the packing process, which results in three new solution approaches. Keeping this decomposition in mind, we model the smaller-dimensional problems in a single position-indexed formulation with non-overlapping inequalities serving as binding constraints. Thus, we come up with a new integer linear programming model, which we subject to polyhedral analysis. Furthermore, we establish general non-overlapping and density inequalities and prove under appropriate assumptions their facet-defining property for the convex hull of the integer solutions. Based on the proposed model and the strong inequalities, we develop a new branch-and-cut algorithm. Being a relaxation of the higher-dimensional problem, each of the smaller-dimensional problems is also relevant for different areas, e.g. for scheduling. To tackle any of these smaller-dimensional problems, we use a Gilmore-Gomory model, which is a Dantzig-Wolfe decomposition of the position-indexed formulation. In order to obtain a contiguous structure for the optimal solution, its basis matrix must have a consecutive 1's property. For construction of such matrices, we develop new branch-and-price algorithms which are distinguished by various strategies for the enumeration of partial solutions. We also prove some characteristics of partial solutions, which tighten the slave problem of column generation. For a nonlinear modeling of the higher-dimensional packing problems, we investigate state-of-the-art constraint programming approaches, modify them, and propose new dichotomy and intersection branching strategies. To tighten the constraint propagation, we introduce new pruning rules. For that, we apply 1D relaxation with intervals and forbidden pairs, an advanced bar relaxation, 2D slice relaxation, and 1D slice-bar relaxation with forbidden pairs. The new rules are based on the relaxation by the smaller-dimensional problems which, in turn, are replaced by a linear programming relaxation of the Gilmore-Gomory model. We conclude with a discussion of implementation issues and numerical studies of all proposed approaches. / Es werden NP-schwere höherdimensionale orthogonale Packungsprobleme betrachtet. Wir untersuchen ihre logische Struktur genauer und zeigen, dass sie sich in Probleme kleinerer Dimension mit einer speziellen Nachbarschaftsstruktur zerlegen lassen. Dies beeinflusst die Modellierung des Packungsprozesses, die ihreseits zu drei neuen Lösungsansätzen führt. Unter Beachtung dieser Zerlegung modellieren wir die Probleme kleinerer Dimension in einer einzigen positionsindizierten Formulierung mit Nichtüberlappungsungleichungen, die als Bindungsbedingungen dienen. Damit entwickeln wir ein neues Modell der ganzzahligen linearen Optimierung und unterziehen dies einer Polyederanalyse. Weiterhin geben wir allgemeine Nichtüberlappungs- und Dichtheitsungleichungen an und beweisen unter geeigneten Annahmen ihre facettendefinierende Eigenschaft für die konvexe Hülle der ganzzahligen Lösungen. Basierend auf dem vorgeschlagenen Modell und den starken Ungleichungen entwickeln wir einen neuen Branch-and-Cut-Algorithmus. Jedes Problem kleinerer Dimension ist eine Relaxation des höherdimensionalen Problems. Darüber hinaus besitzt es Anwendungen in verschiedenen Bereichen, wie zum Beispiel im Scheduling. Für die Behandlung der Probleme kleinerer Dimension setzen wir das Gilmore-Gomory-Modell ein, das eine Dantzig-Wolfe-Dekomposition der positionsindizierten Formulierung ist. Um eine Nachbarschaftsstruktur zu erhalten, muss die Basismatrix der optimalen Lösung die consecutive-1’s-Eigenschaft erfüllen. Für die Konstruktion solcher Matrizen entwickeln wir neue Branch-and-Price-Algorithmen, die sich durch Strategien zur Enumeration von partiellen Lösungen unterscheiden. Wir beweisen auch einige Charakteristiken von partiellen Lösungen, die das Hilfsproblem der Spaltengenerierung verschärfen. Für die nichtlineare Modellierung der höherdimensionalen Packungsprobleme untersuchen wir moderne Ansätze des Constraint Programming, modifizieren diese und schlagen neue Dichotomie- und Überschneidungsstrategien für die Verzweigung vor. Für die Verstärkung der Constraint Propagation stellen wir neue Ablehnungskriterien vor. Wir nutzen dabei 1D Relaxationen mit Intervallen und verbotenen Paaren, erweiterte Streifen-Relaxation, 2D Scheiben-Relaxation und 1D Scheiben-Streifen-Relaxation mit verbotenen Paaren. Alle vorgestellten Kriterien basieren auf Relaxationen durch Probleme kleinerer Dimension, die wir weiter durch die LP-Relaxation des Gilmore-Gomory-Modells abschwächen. Wir schließen mit Umsetzungsfragen und numerischen Experimenten aller vorgeschlagenen Ansätze.

Includes insert: Conclusion / Bibliography: leaves cccxxxiii-ccclx / xiii, ccclx p., [9] leaves of plates : ill ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Politics, 1986

Zugl.: Karlsruhe, University, Diss., 2006.

Zugl.: Hamburg, Techn. Univ., Diss., 2006

Zugl.: Erlangen, Nürnberg, University, Diss., 2008.

Thesis (M.S.)--University of North Carolina Wilmington, 2008. / Title from PDF title page (viewed September 24, 2008) Includes bibliographical references (p. 46-47)

Würzburg, Univ., Diss., 2009