A scalable analysis framework for large-scale RDF data

With the growth of the Semantic Web, the availability of RDF datasets from multiple domains as Linked Data has taken the corpora of this web to a terabyte-scale, and challenges modern knowledge storage and discovery techniques. Research and engineering on RDF data management systems is a very active area with many standalone systems being introduced. However, as the size of RDF data increases, such single-machine approaches meet performance bottlenecks, in terms of both data loading and querying, due to the limited parallelism inherent to symmetric multi-threaded systems and the limited available system I/O and system memory. Although several approaches for distributed RDF data processing have been proposed, along with clustered versions of more traditional approaches, their techniques are limited by the trade-off they exploit between loading complexity and query efficiency in the presence of big RDF data. This thesis then, introduces a scalable analysis framework for processing large-scale RDF data, which focuses on various techniques to reduce inter-machine communication, computation and load-imbalancing so as to achieve fast data loading and querying on distributed infrastructures. The first part of this thesis focuses on the study of RDF store implementation and parallel hashing on big data processing. (1) A system-level investigation of RDF store implementation has been conducted on the basis of a comparative analysis of runtime characteristics of a representative set of RDF stores. The detailed time cost and system consumption is measured for data loading and querying so as to provide insight into different triple store implementation as well as an understanding of performance differences between different platforms. (2) A high-level structured parallel hashing approach over distributed memory is proposed and theoretically analyzed. The detailed performance of hashing implementations using different lock-free strategies has been characterized through extensive experiments, thereby allowing system developers to make a more informed choice for the implementation of their high-performance analytical data processing systems. The second part of this thesis proposes three main techniques for fast processing of large RDF data within the proposed framework. (1) A very efficient parallel dictionary encoding algorithm, to avoid unnecessary disk-space consumption and reduce computational complexity of query execution. The presented implementation has achieved notable speedups compared to the state-of-art method and also has achieved excellent scalability. (2) Several novel parallel join algorithms, to efficiently handle skew over large data during query processing. The approaches have achieved good load balancing and have been demonstrated to be faster than the state-of-art techniques in both theoretical and experimental comparisons. (3) A two-tier dynamic indexing approach for processing SPARQL queries has been devised which keeps loading times low and decreases or in some instances removes intermachine data movement for subsequent queries that contain the same graph patterns. The results demonstrate that this design can load data at least an order of magnitude faster than a clustered store operating in RAM while remaining within an interactive range for query processing and even outperforms current systems for various queries

Kiel Declarative Programming Days 2013

This report contains the papers presented at the Kiel Declarative Programming Days 2013, held in Kiel (Germany) during September 11-13, 2013. The Kiel Declarative Programming Days 2013 unified the following events: * 20th International Conference on Applications of Declarative Programming and Knowledge Management (INAP 2013) * 22nd International Workshop on Functional and (Constraint) Logic Programming (WFLP 2013) * 27th Workshop on Logic Programming (WLP 2013) All these events are centered around declarative programming, an advanced paradigm for the modeling and solving of complex problems. These specification and implementation methods attracted increasing attention over the last decades, e.g., in the domains of databases and natural language processing, for modeling and processing combinatorial problems, and for high-level programming of complex, in particular, knowledge-based systems

Resource-aware Programming in a High-level Language - Improved performance with manageable effort on clustered MPSoCs

Bis 2001 bedeutete Moores und Dennards Gesetz eine Verdoppelung der Ausführungszeit alle 18 Monate durch verbesserte CPUs. Heute ist Nebenläufigkeit das dominante Mittel zur Beschleunigung von Supercomputern bis zu mobilen Geräten. Allerdings behindern neuere Phänomene wie "Dark Silicon" zunehmend eine weitere Beschleunigung durch Hardware. Um weitere Beschleunigung zu erreichen muss sich auch die Soft­ware mehr ihrer Hardware Resourcen gewahr werden. Verbunden mit diesem Phänomen ist eine immer heterogenere Hardware. Supercomputer integrieren Beschleuniger wie GPUs. Mobile SoCs (bspw. Smartphones) integrieren immer mehr Fähigkeiten. Spezialhardware auszunutzen ist eine bekannte Methode, um den Energieverbrauch zu senken, was ein weiterer wichtiger Aspekt ist, welcher mit der reinen Geschwindigkeit abgewogen werde muss. Zum Beispiel werden Supercomputer auch nach "Performance pro Watt" bewertet. Zur Zeit sind systemnahe low-level Programmierer es gewohnt über Hardware nachzudenken, während der gemeine high-level Programmierer es vorzieht von der Plattform möglichst zu abstrahieren (bspw. Cloud). "High-level" bedeutet nicht, dass Hardware irrelevant ist, sondern dass sie abstrahiert werden kann. Falls Sie eine Java-Anwendung für Android entwickeln, kann der Akku ein wichtiger Aspekt sein. Irgendwann müssen aber auch Hochsprachen resourcengewahr werden, um Geschwindigkeit oder Energieverbrauch zu verbessern. Innerhalb des Transregio "Invasive Computing" habe ich an diesen Problemen gearbeitet. In meiner Dissertation stelle ich ein Framework vor, mit dem man Hochsprachenanwendungen resourcengewahr machen kann, um so die Leistung zu verbessern. Das könnte beispielsweise erhöhte Effizienz oder schnellerer Ausführung für das System als Ganzes bringen. Ein Kerngedanke dabei ist, dass Anwendungen sich nicht selbst optimieren. Stattdessen geben sie alle Informationen an das Betriebssystem. Das Betriebssystem hat eine globale Sicht und trifft Entscheidungen über die Resourcen. Diesen Prozess nennen wir "Invasion". Die Aufgabe der Anwendung ist es, sich an diese Entscheidungen anzupassen, aber nicht selbst welche zu fällen. Die Herausforderung besteht darin eine Sprache zu definieren, mit der Anwendungen Resourcenbedingungen und Leistungsinformationen kommunizieren. So eine Sprache muss ausdrucksstark genug für komplexe Informationen, erweiterbar für neue Resourcentypen, und angenehm für den Programmierer sein. Die zentralen Beiträge dieser Dissertation sind: Ein theoretisches Modell der Resourcen-Verwaltung, um die Essenz des resourcengewahren Frameworks zu beschreiben, die Korrektheit der Entscheidungen des Betriebssystems bezüglich der Bedingungen einer Anwendung zu begründen und zum Beweis meiner Thesen von Effizienz und Beschleunigung in der Theorie. Ein Framework und eine Übersetzungspfad resourcengewahrer Programmierung für die Hochsprache X10. Zur Bewertung des Ansatzes haben wir Anwendungen aus dem High Performance Computing implementiert. Eine Beschleunigung von 5x konnte gemessen werden. Ein Speicherkonsistenzmodell für die X10 Programmiersprache, da dies ein notwendiger Schritt zu einer formalen Semantik ist, die das theoretische Modell und die konkrete Implementierung verknüpft. Zusammengefasst zeige ich, dass resourcengewahre Programmierung in Hoch\-sprachen auf zukünftigen Architekturen mit vielen Kernen mit vertretbarem Aufwand machbar ist und die Leistung verbessert

Safe and scalable parallel programming with session types

Parallel programming is a technique that can coordinate and utilise multiple hardware resources simultaneously, to improve the overall computation performance. However, reasoning about the communication interactions between the resources is difficult. Moreover, scaling an application often leads to increased number and complexity of interactions, hence we need a systematic way to ensure the correctness of the communication aspects of parallel programs. In this thesis, we take an interaction-centric view of parallel programming, and investigate applying and adapting the theory of Session Types, a formal typing discipline for structured interaction-based communication, to guarantee the lack of communication mismatches and deadlocks in concurrent systems. We focus on scalable, distributed parallel systems that use message-passing for communication. We explore programming language primitives, tools and frameworks to simplify parallel programming. First, we present the design and implementation of Session C, a program ming toolchain for message-passing parallel programming. Session C can ensure deadlock freedom, communication safety and global progress through static type checking, and supports optimisations by refinements through session subtyping. Then we introduce Pabble, a protocol description language for designing parametric interaction protocols. The language can capture scalable interaction patterns found in parallel applications, and guarantees communication-safety and deadlock-freedom despite the undecidability of the underlying parameterised session type theory. Next, we demonstrate an application of Pabble in a workflow that combines Pabble protocols and computation kernel code describing the sequential computation behaviours, to generate a Message-Passing Interface (MPI) parallel application. The framework guarantees, by construction, that generated code are free from communication errors and deadlocks. Finally, we formalise an extension of binary session types and new language primitives for safe and efficient implementations of multiparty parallel applications in a binary server-client programming environment. Our exploration with session-based parallel programming shows that it is a feasible and practical approach to guaranteeing communication aspects of complex, interaction-based scalable parallel programming.Open Acces

Link prediction in large directed graphs

The first chapter introduces an approach to machine learning (ML) were data is understood as a network of connected entities. This strategy seeks inter-entity information for knowledge discovery, in contrast with traditional intra-entity approaches based on instances and their features. We discuss the importance of this connectivist ML (which we refer to as graph mining) in the current context where large, topology-based data sets have been made available. Chapter ends by introducing the Link Prediction (LP) problem, together with its current computational and performance limitations. The second chapter discusses early contributions to graph mining, and introduces problems frequently tackled through this paradigm. Later the chapter focuses on the state-of-the-art of LP. It presents three different approaches to the problem of finding links in a relational set, and argues about the importance of the most computationally scalable one: similarity-based algorithms. It categorizes similarity-based algorithms in three types of LP scores. For the most scalable type, local similarity-based algorithms, the chapter identifies and formally describes the most competitive proposals according to the bibliography. Chapter three analyses the LP problem, partly as a classic binary classification problem. A list of graph properties such as directionality, weights and time are discussed in the context of LP. Follows a formal time and space complexity analysis of similarity-based scores of LP. The chapter ends with an study of the class imbalance found in LP problems. In chapter four a novel similarity-based score of LP is introduced. The chapter first elaborates on the importance of hierarchies for representing knowledge through directed graphs. Several modifications to the proposed score are also defined. This chapter presents a modified version of the most competitive undirected scores of LP, to adapt them to directed graphs. The evaluation methodologies of LP are analyzed in the fifth chapter. It starts by discussing the problem of evaluating domains with a huge class imbalance, identifying the most appropriate methodologies for it. A modification of the most appropriate evaluation methodology according to the bibliography is presented, with the goal of focusing on relevant predictions. Follows a discussion on the faithful estimation of the precision of predictors. Chapter six describes the graphs used for score evaluation, as well as how data was transformed into a directed graph. Reasons on why these particular domains were chosen are given, making a special case of webgraphs and their well known relation with hierarchies. The most basic properties of each resultant graph are shown. Tests performed are presented in chapter seven. The three most competitive LP scores currently available are tested among themselves, and against a proposed version of those same scores for directed graphs. Our proposed score and its modifications are tested against the scores obtaining the best results in the previous tests. The case of LP in webgraphs is considered separately, testing six different webgraphs. The chapter ends with a discussion on the limitations of this formal analysis, showing examples of predictions obtained. Chapter eight includes the computational aspects of the work done. It starts with a discussion on the importance of memory management for determining the computational cost of LP algorithms. A proposal on how to reduce this cost through precision reduction is presented. Follows a section focused on the parallelization of code, which includes two different implementations on one graph-specific programming model (Pregel) and on one generic programming model (OpenMP). The chapter ends with a specification of the computational resources used for the tests done. The conclusions of this thesis proposal are presented in nine. Chapter ten contains several future lines of work.El primer capítol introdueix una perspectiva de l'aprenentatge automàtic on les dades s'entén com una xarxa d'entitats connectades. Aquesta estratègia es centra en les relacions entre entitats per aprendre, en contrast amb les solucions tradicionals basades en instancies i els seus atributs. Discutim sobre la importància d'aquesta perspectiva connectivista (a la que ens referim com mineria de grafs) en el context actual on grans conjunts de dades basats en xarxes estan apareixent. El capítol finalitza amb la presentació del problema de Predicció d'Arestes (PA), junt amb una primera anàlisi de les seves limitacions actuals. El segon capítol presenta les primeres contribucions a la mineria de grafs, introduint problemes típicament solucionats mitjançant aquest paradigma. El capítol es centra en l'estat de l'art de PA. Presenta tres solucions diferents per al problema i argumenta la importància del més computacionalment escalable: els algoritmes basats en similitud. Categoritza aquests en tres tipus, i per als més escalables d'aquests, els algoritmes locals, s'identifica i es descriu formalment les propostes més competitives d'acord amb la bibliografia. El tercer capítol analitza el problema de PA, inicialment com a problema de classificació binari. Una llista de propietats de grafs són discutides en el context de la PA, com la direccionalitat o els pesos. Segueix una anàlisi del cost computacional en temps com en espai, dels algorismes basats en similitud. El capítol finalitza amb un estudi del desbalanceig de classes, freqüent en la PA. Al capítol quatre es presenta un nou algorisme basat en similitud per la PA. El capítol elabora sobre la importància de les jerarquies a la representació del coneixement a través de grafs dirigits. Varies modificacions es proposen per al nou algorisme. Aquest capítol també inclou una modificació sobre els actuals algorismes de similitud per a grafs no dirigits, per adaptar-los per a grafs dirigits. Les metodologies d'avaluació de la PA s'analitzen al cinquè capítol. Comença amb una discussió sobre els problemes que suposa avaluar un context amb un gran desbalanceig de classes, identificant les metodologies apropiades per aquests casos. Es proposa una modificació sobre el mètode més apropiat actualment disponible, per tal de centrar-se en les prediccions rellevants. Segueix una discussió sobre l'estimació fidedigna de la precisió dels predictors. El sisè capítol descriu els grafs usats per avaluar els algorismes, així com la metodologia usada per transformar-los en grafs dirigits. Les raons per triar aquest conjunt de grafs són exposades, posant especial interès al cas dels grafs web i a la seva ben coneguda relació amb les jerarquies. Les propietats més bàsiques de cada graf resultant són descrites. Els tests efectuats es mostren al capítol setè. Els tres algorismes actuals de PA més competitius són comparats amb ells mateixos i amb la versió per a grafs dirigits definida anteriorment. L'algorisme proposat anteriorment i les seves modificacions també són avaluats. El problema de la PA en grafs web es considera per separat, avaluant sis grafs web diferents. El capítol acaba amb una discussió sobre les limitacions de les avaluacions formals, mostrant exemples de prediccions obtingudes. El vuitè capítol inclou els aspectes computacionals de la tesi. Comença amb una discussió sobre la importància de la gestió de memòria per a la definició del cost computacional dels algorismes de PA. Inclou una proposta sobre com reduir aquest cost mitjançant una reducció en la precisió. Segueix una secció centrada en la paral·lelització del codi, que inclou dues implementacions diferents, una en un model de programació específic per grafs (Pregel) i una amb un model de programació paral·lela genèric (OpenMP). El capítol finalitza amb una especificació dels recursos computacionals usats per als tests realitzats. Les conclusions de la tesi es presenten al capítol novè, i les línies de treball futur al des

Towards Next Generation Sequential and Parallel SAT Solvers

This thesis focuses on improving the SAT solving technology. The improvements focus on two major subjects: sequential SAT solving and parallel SAT solving. To better understand sequential SAT algorithms, the abstract reduction system Generic CDCL is introduced. With Generic CDCL, the soundness of solving techniques can be modeled. Next, the conflict driven clause learning algorithm is extended with the three techniques local look-ahead, local probing and all UIP learning that allow more global reasoning during search. These techniques improve the performance of the sequential SAT solver Riss. Then, the formula simplification techniques bounded variable addition, covered literal elimination and an advanced cardinality constraint extraction are introduced. By using these techniques, the reasoning of the overall SAT solving tool chain becomes stronger than plain resolution. When using these three techniques in the formula simplification tool Coprocessor before using Riss to solve a formula, the performance can be improved further. Due to the increasing number of cores in CPUs, the scalable parallel SAT solving approach iterative partitioning has been implemented in Pcasso for the multi-core architecture. Related work on parallel SAT solving has been studied to extract main ideas that can improve Pcasso. Besides parallel formula simplification with bounded variable elimination, the major extension is the extended clause sharing level based clause tagging, which builds the basis for conflict driven node killing. The latter allows to better identify unsatisfiable search space partitions. Another improvement is to combine scattering and look-ahead as a superior search space partitioning function. In combination with Coprocessor, the introduced extensions increase the performance of the parallel solver Pcasso. The implemented system turns out to be scalable for the multi-core architecture. Hence iterative partitioning is interesting for future parallel SAT solvers. The implemented solvers participated in international SAT competitions. In 2013 and 2014 Pcasso showed a good performance. Riss in combination with Copro- cessor won several first, second and third prices, including two Kurt-Gödel-Medals. Hence, the introduced algorithms improved modern SAT solving technology

Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design – FMCAD 2021

The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing

Validity contracts for software transactions

Software Transactional Memory is a promising approach to concurrent programming, freeing programmers from error-prone concurrency control decisions that are complicated and not composable. But few such systems address consistencies of transactional objects. In this thesis, I propose a contract-based transactional programming model toward more secure transactional softwares. In this general model, a validity contract specifies both requirements and effects for transactions. Validity contracts bring numerous benefits including reasoning about and verifying transactional programs, detecting and resolving transactional conflicts, automating object revalidation and easing program debugging. I introduce an ownership-based framework, namely AVID, derived from the general model, using object ownership as a mechanism for specifying and reasoning validity contracts. I have specified a formal type system and implemented a prototype type checker to support static checking. I also have built a transactional library framework AVID, based on existing Java DSTM2 framework, for expressing transactions and validity contracts. Experimental results on a multi-core system show that contracts add little overheads to the original STM. I find that contract-aware contention management yields significant speedups in some cases. The results have suggested compiler directed optimisation for tunning contract-based transactional programs. My further work will investigate the applications of transaction contracts on various aspects of TM research such as hardware support and open-nesting