Performance Improvements Using Dynamic Performance Stubs

This thesis proposes a new methodology to extend the software performance engineering process. Common performance measurement and tuning principles mainly target to improve the software function itself. Hereby, the application source code is studied and improved independently of the overall system performance behavior. Moreover, the optimization of the software function has to be done without an estimation of the expected optimization gain. This often leads to an under- or overoptimization, and hence, does not utilize the system sufficiently. The proposed performance improvement methodology and framework, called dynamic performance stubs, improves the before mentioned insufficiencies by evaluating the overall system performance improvement. This is achieved by simulating the performance behavior of the original software functionality depending on an adjustable optimization level prior to the real optimization. So, it enables the software performance analyst to determine the systems’ overall performance behavior considering possible outcomes of different improvement approaches. Moreover, by using the dynamic performance stubs methodology, a cost-benefit analysis of different optimizations regarding the performance behavior can be done. The approach of the dynamic performance stubs is to replace the software bottleneck by a stub. This stub combines the simulation of the software functionality with the possibility to adjust the performance behavior depending on one or more different performance aspects of the replaced software function. A general methodology for using dynamic performance stubs as well as several methodologies for simulating different performance aspects is discussed. Finally, several case studies to show the application and usability of the dynamic performance stubs approach are presented

A practical guide to computer simulations

Here practical aspects of conducting research via computer simulations are discussed. The following issues are addressed: software engineering, object-oriented software development, programming style, macros, make files, scripts, libraries, random numbers, testing, debugging, data plotting, curve fitting, finite-size scaling, information retrieval, and preparing presentations. Because of the limited space, usually only short introductions to the specific areas are given and references to more extensive literature are cited. All examples of code are in C/C++.Comment: 69 pages, with permission of Wiley-VCH, see http://www.wiley-vch.de (some screenshots with poor quality due to arXiv size restrictions) A comprehensively extended version will appear in spring 2009 as book at Word-Scientific, see http://www.worldscibooks.com/physics/6988.htm

CROCHET: Checkpoint and Rollback via Lightweight Heap Traversal on Stock JVMs

Checkpoint/rollback (CR) mechanisms create snapshots of the state of a running application, allowing it to later be restored to that checkpointed snapshot. Support for checkpoint/rollback enables many program analyses and software engineering techniques, including test generation, fault tolerance, and speculative execution. Fully automatic CR support is built into some modern operating systems. However, such systems perform checkpoints at the coarse granularity of whole pages of virtual memory, which imposes relatively high overhead to incrementally capture the changing state of a process, and makes it difficult for applications to checkpoint only some logical portions of their state. CR systems implemented at the application level and with a finer granularity typically require complex developer support to identify: (1) where checkpoints can take place, and (2) which program state needs to be copied. A popular compromise is to implement CR support in managed runtime environments, e.g. the Java Virtual Machine (JVM), but this typically requires specialized, non-standard runtime environments, limiting portability and adoption of this approach. In this paper, we present a novel approach for Checkpoint ROllbaCk via lightweight HEap Traversal (Crochet), which enables fully automatic fine-grained lightweight checkpoints within unmodified commodity JVMs (specifically Oracle\u27s HotSpot and OpenJDK). Leveraging key insights about the internal design common to modern JVMs, Crochet works entirely through bytecode rewriting and standard debug APIs, utilizing special proxy objects to perform a lazy heap traversal that starts at the root references and traverses the heap as objects are accessed, copying or restoring state as needed and removing each proxy immediately after it is used. We evaluated Crochet on the DaCapo benchmark suite, finding it to have very low runtime overhead in steady state (ranging from no overhead to 1.29x slowdown), and that it often outperforms a state-of-the-art system-level checkpoint tool when creating large checkpoints

Cache performance of chronological garbage collection

This thesis presents cache performance analysis of the Chronological Garbage Collection Algorithm used in LVM system. LVM is a new Logic Virtual Machine for Prolog. It adopts one stack policy for all dynamic memory requirements and cooperates with an efficient garbage collection algorithm, the Chronological Garbage Collection, to recycle space, not as a deliberate garbage collection operation, but as a natural activity of the LVM engine to gather useful objects. This algorithm combines the advantages of the traditional copying, mark-compact, generational, and incremental garbage collection schemes. In order to determine the improvement of cache performance under our garbage- collection algorithm, we developed a simulator to do trace-driven cache simulation. Direct-mapped cache and set-associative cache with different cache sizes, write policies, block sizes and set associativities are simulated and measured. A comparison of LVM and SICStus 3.1 for the same benchmarks was performed. From the simulation results, we found important factors influencing the performance of the CGC algorithm. Meanwhile, the results from the cache simulator fully support the experimental results gathered from the LVM system: the cost of CGC Is almost paid by the improved cache performance. Further, we found that the memory reference patterns of our benchmarks share the same properties: most writes are for allocation and most reads are to recently written objects. In addition, the results also showed that the write-miss policy can have a dramatic effect on the cache performance of the benchmarks and a write-validate policy gives the best performance. The comparison shows that when the input size of benchmarks is small, SICStus is about 3-8 times faster than LVM. This is an acceptable range of performance ratio for comparing a binary-code engine against a byte-code emulator. When we increase the input sizes, some benchmarks maintain this performance ratio, whereas others greatly narrow the performance gap and at certain breakthrough points perform better than their counterparts under SICStus

Information Flow Control with System Dependence Graphs - Improving Modularity, Scalability and Precision for Object Oriented Languages

Die vorliegende Arbeit befasst sich mit dem Gebiet der statischen Programmanalyse — insbesondere betrachten wir Analysen, deren Ziel es ist, bestimmte Sicherheitseigenschaften, wie etwa Integrität und Vertraulichkeit, für Programme zu garantieren. Hierfür verwenden wir sogenannte Abhängigkeitsgraphen, welche das potentielle Verhalten des Programms sowie den Informationsfluss zwischen einzelnen Programmpunkten abbilden. Mit Hilfe dieser Technik können wir sicherstellen, dass z.B. ein Programm keinerlei Information über ein geheimes Passwort preisgibt. Im Speziellen liegt der Fokus dieser Arbeit auf Techniken, die das Erstellen des Abhängigkeitsgraphen verbessern, da dieser die Grundlage für viele weiterführende Sicherheitsanalysen bildet. Die vorgestellten Algorithmen und Verbesserungen wurden in unser Analysetool Joana integriert und als Open-Source öffentlich verfügbar gemacht. Zahlreiche Kooperationen und Veröffentlichungen belegen, dass die Verbesserungen an Joana auch in der Forschungspraxis relevant sind. Diese Arbeit besteht im Wesentlichen aus drei Teilen. Teil 1 befasst sich mit Verbesserungen bei der Berechnung des Abhängigkeitsgraphen, Teil 2 stellt einen neuen Ansatz zur Analyse von unvollständigen Programmen vor und Teil 3 zeigt aktuelle Verwendungsmöglichkeiten von Joana an konkreten Beispielen. Im ersten Teil gehen wir detailliert auf die Algorithmen zum Erstellen eines Abhängigkeitsgraphen ein, dabei legen wir besonderes Augenmerk auf die Probleme und Herausforderung bei der Analyse von Objektorientierten Sprachen wie Java. So stellen wir z.B. eine Analyse vor, die den durch Exceptions ausgelösten Kontrollfluss präzise behandeln kann. Hauptsächlich befassen wir uns mit der Modellierung von Seiteneffekten, die bei der Kommunikation über Methodengrenzen hinweg entstehen können. Bei Abhängigkeitsgraphen werden Seiteneffekte, also Speicherstellen, die von einer Methode gelesen oder verändert werden, in Form von zusätzlichen Knoten dargestellt. Dabei zeigen wir, dass die Art und Weise der Darstellung, das sogenannte Parametermodel, enormen Einfluss sowohl auf die Präzision als auch auf die Laufzeit der gesamten Analyse hat. Wir erklären die Schwächen des alten Parametermodels, das auf Objektbäumen basiert, und präsentieren unsere Verbesserungen in Form eines neuen Modells mit Objektgraphen. Durch das gezielte Zusammenfassen von redundanten Informationen können wir die Anzahl der berechneten Parameterknoten deutlich reduzieren und zudem beschleunigen, ohne dabei die Präzision des resultierenden Abhängigkeitsgraphen zu verschlechtern. Bereits bei kleineren Programmen im Bereich von wenigen tausend Codezeilen erreichen wir eine im Schnitt 8-fach bessere Laufzeit — während die Präzision des Ergebnisses in der Regel verbessert wird. Bei größeren Programmen ist der Unterschied sogar noch deutlicher, was dazu führt, dass einige unserer Testfälle und alle von uns getesteten Programme ab einer Größe von 20000 Codezeilen nur noch mit Objektgraphen berechenbar sind. Dank dieser Verbesserungen kann Joana mit erhöhter Präzision und bei wesentlich größeren Programmen eingesetzt werden. Im zweiten Teil befassen wir uns mit dem Problem, dass bisherige, auf Abhängigkeitsgraphen basierende Sicherheitsanalysen nur vollständige Programme analysieren konnten. So war es z.B. unmöglich, Bibliothekscode ohne Kenntnis aller Verwendungsstellen zu betrachten oder vorzuverarbeiten. Wir entdeckten bei der bestehenden Analyse eine Monotonie-Eigenschaft, welche es uns erlaubt, Analyseergebnisse von Programmteilen auf beliebige Verwendungsstellen zu übertragen. So lassen sich zum einen Programmteile vorverarbeiten und zum anderen auch generelle Aussagen über die Sicherheitseigenschaften von Programmteilen treffen, ohne deren konkrete Verwendungsstellen zu kennen. Wir definieren die Monotonie-Eigenschaft im Detail und skizzieren einen Beweis für deren Korrektheit. Darauf aufbauend entwickeln wir eine Methode zur Vorverarbeitung von Programmteilen, die es uns ermöglicht, modulare Abhängigkeitsgraphen zu erstellen. Diese Graphen können zu einem späteren Zeitpunkt der jeweiligen Verwendungsstelle angepasst werden. Da die präzise Erstellung eines modularen Abhängigkeitsgraphen sehr aufwendig werden kann, entwickeln wir einen Algorithmus basierend auf sogenannten Zugriffspfaden, der die Skalierbarkeit verbessert. Zuletzt skizzieren wir einen Beweis, der zeigt, dass dieser Algorithmus tatsächlich immer eine konservative Approximation des modularen Graphen berechnet und deshalb die Ergebnisse darauf aufbauender Sicherheitsanalysen weiterhin gültig sind. Im dritten Teil präsentieren wir einige erfolgreiche Anwendungen von Joana, die im Rahmen einer Kooperation mit Ralf Küsters von der Universität Trier entstanden sind. Hier erklären wir zum einen, wie man unser Sicherheitswerkzeug Joana generell verwenden kann. Zum anderen zeigen wir, wie in Kombination mit weiteren Werkzeugen und Techniken kryptographische Sicherheit für ein Programm garantiert werden kann - eine Aufgabe, die bisher für auf Informationsfluss basierende Analysen nicht möglich war. In diesen Anwendungen wird insbesondere deutlich, wie die im Rahmen dieser Arbeit vereinfachte Bedienung die Verwendung von Joana erleichtert und unsere Verbesserungen der Präzision des Ergebnisses die erfolgreiche Analyse erst ermöglichen

Compiling Prolog to Logic-inference Virtual Machine

The Logic-inference Virtual Machine (LVM) is a new Prolog execution model consisting of a set of high-level instructions and memory architecture for handling control and unification. Different from the well-known Warren's Abstract Machine [1], which uses Structure Copying method, the LVM adopts a hybrid of Program Sharing [2] and Structure Copying to represent first-order terms. In addition, the LVM employs a single stack paradigm for dynamic memory allocation and embeds a very efficient garbage collection algorithm to reclaim the useless memory cells. In order to construct a complete Prolog system based on the LVM, a corresponding compiler must be written. In this thesis, a design of such LVM compiler is presented and all important components of the compiler are described. The LVM compiler is developed to translate Prolog programs into LVM bytecode instructions, so that a Prolog program is compiled once and can run anywhere. The first version of LVM compiler (about 8000 lines of C code) has been developed. The compilation time is approximately proportional to the size of source codes. About 80 percent of the time are spent on the global analysis. Some compiled programs have been tested under a LVM emulator. Benchmarks show that the LVM system is very promising in memory utilization and performance

Building CPU stubs to optimize CPU bound systems: An application of dynamic performance stubs.

Dynamic performance stubs provide a framework for the simulation of the performance behavior of software modules and functions. Hence, they can be used as an exten- sion to software performance engineering methodologies. The methodology of dynamic performance stubs can be used for a gain oriented performance improvement. It is also possible to identify “hidden” bottlenecks and to prioritize optimization possibilities. Nowadays, the processing power of CPUs is mainly increased by adding more cores to the architecture. To have benefits from this, new software is mostly designed for parallel processing, especially, in large software projects. As software performance optimizations can be difficult in these environments, new methodologies have to be defined. This paper evaluates a possibility to simulate the functional behavior of software algorithms by the use of the simulated software functionality. These can be used by the dynamic performance stub framework, e.g., to build a CPU stub, to replace the algorithm. Thus, it describes a methodology as well as an implementation and evaluates both in an industrial case study. Moreover, it presents an extension to the CPU stubs by applying these stubs to simulate multi-threaded applications. The extension is evaluated by a case study as well. We show show that the functionality of software algorithms can be replaced by software simulation functions. This stubbing approach can be used to create dynamic performance stubs, such as CPU stubs. Additionally, we show that the concept of CPU stubs can be applied to multi-threaded applications

Lazy Sequentialization for TSO and PSO via Shared Memory Abstractions

Lazy sequentialization is one of the most effective approaches for the bounded verification of concurrent programs. Existing tools assume sequential consistency (SC), thus the feasibility of lazy sequentializations for weak memory models (WMMs) remains untested. Here, we describe the first lazy sequentialization approach for the total store order (TSO) and partial store order (PSO) memory models. We replace all shared memory accesses with operations on a shared memory abstraction (SMA), an abstract data type that encapsulates the semantics of the underlying WMM and implements it under the simpler SC model. We give efficient SMA implementations for TSO and PSO that are based on temporal circular doubly-linked lists, a new data structure that allows an efficient simulation of the store buffers. We show experimentally, both on the SV-COMP concurrency benchmarks and a real world instance, that this approach works well in combination with lazy sequentialization on top of bounded model checking