Workload characterization of JVM languages

Being developed with a single language in mind, namely Java, the Java Virtual Machine (JVM) nowadays is targeted by numerous programming languages. Automatic memory management, Just-In-Time (JIT) compilation, and adaptive optimizations provided by the JVM make it an attractive target for different language implementations. Even though being targeted by so many languages, the JVM has been tuned with respect to characteristics of Java programs only -- different heuristics for the garbage collector or compiler optimizations are focused more on Java programs. In this dissertation, we aim at contributing to the understanding of the workloads imposed on the JVM by both dynamically-typed and statically-typed JVM languages. We introduce a new set of dynamic metrics and an easy-to-use toolchain for collecting the latter. We apply our toolchain to applications written in six JVM languages -- Java, Scala, Clojure, Jython, JRuby, and JavaScript. We identify differences and commonalities between the examined languages and discuss their implications. Moreover, we have a close look at one of the most efficient compiler optimizations - method inlining. We present the decision tree of the HotSpot JVM's JIT compiler and analyze how well the JVM performs in inlining the workloads written in different JVM languages

The Relationship Between Teachers\u27 Perception of Data-Driven Instructional Leadership and Their Sense of Efficacy and Anxiety for Data-Driven Decision-Making

The purpose of this study was to ascertain the relationship between teachers’ perception of data-driven instructional leadership and their sense of self-efficacy and anxiety towards data-driven decision-making. Additionally, the research study examined if teachers’ school level (elementary or secondary) influenced their perception of data-driven instructional leadership and their sense of self-efficacy and anxiety towards data-driven decision-making. The researcher utilized a correlational research design and correlational/regression analysis to conduct this study based on the theoretical framework of Bandura’s social learning theory. The researcher surveyed 300 full-time certified educators in a rural school district located in the southeastern United States using the Data-informed School Leadership Framework (DISL) and Data-driven Decision-making (DDDM) Efficacy and Anxiety instruments (3D-MEA). The results of the correlational analysis indicated a strong positive relationship indicating that those with higher DISL scores tended to report higher DDDM efficacy. The results of the correlational analysis also indicated that a significant relationship did not exist between DISL scores and DDDM anxiety. Finally, multiple regression analyses revealed that data-driven instructional leadership was a significant predictor of DDDM efficacy; however, data-driven instructional leadership was not a significant predictor of DDDM anxiety. In addition, school level was not significant in either equation reflecting similar findings at both the elementary and secondary levels

Feature based workshop oriented NC planning for asymmetric rotational parts

This thesis describes research which is aimed at devising a framework for a feature based workshop oriented NC planning. The principal objective of this thesis is to utilize a feature based method which can rationalize and enhance part description and in particular part planning and programming on the shop-floor. This work has been done taking into account new developments in the area of shop floor programming. The importance of the techniques and conventions which are addressed in this thesis stems from the recognition that the most effective way to improve and enhance part description is to capture the intent of the engineering drawing by devising a medium in which the recurring patterns of turned components can be modelled for machining. Experimental application software which allows the user to describe the workpiece and subsequently generate the manufacturing code has been realized

Translating Marine Animal Tracking Data into Conservation Policy and Management

There have been efforts around the globe to track individuals of many marine species and assess their movements and distribution with the putative goal of supporting their conservation and management. Determining whether, and how, tracking data have been successfully applied to address real-world conservation issues is however difficult. Here, we compile a broad range of case studies from diverse marine taxa to show how tracking data have helped inform conservation policy and management, including reductions in fisheries bycatch and vessel strikes, and the design and administration of marine protected areas and important habitats. Using these examples, we highlight pathways through which the past and future investment in collecting animal tracking data might be better used to achieve tangible conservation benefits

Engineering for a changing world: 60th Ilmenau Scientific Colloquium, Technische Universität Ilmenau, September 04-08, 2023 : programme

In 2023, the Ilmenau Scientific Colloquium is once more organised by the Department of Mechanical Engineering. The title of this year’s conference “Engineering for a Changing World” refers to limited natural resources of our planet, to massive changes in cooperation between continents, countries, institutions and people – enabled by the increased implementation of information technology as the probably most dominant driver in many fields. The Colloquium, supplemented by workshops, is characterised but not limited to the following topics: – Precision engineering and measurement technology Nanofabrication – Industry 4.0 and digitalisation in mechanical engineering – Mechatronics, biomechatronics and mechanism technology – Systems engineering – Productive teaming - Human-machine collaboration in the production environment The topics are oriented on key strategic aspects of research and teaching in Mechanical Engineering at our university

Atomic Level Computational Studies of Ionic Defects and Transport Properties of Solid State Ionic Conductors

Solid state ionic conductors (or electrolytes) are a vital component for electrochemical devices or systems for chemical and energy transformation. The chemical composition, crystal structure, defects, morphology, and electronic structure of these materials greatly affect their electrochemical properties such as ionic and electronic conductivity. Similar to barium zirconate (BaZrO3), barium hafnate (BaHfO3) is one of the most promising proton-conducting electrolytes for solid oxide fuel cells (SOFCs) because of their high proton conductivity at 400~700 °C. In this study, I have investigated dopant solubility, proton concentration, mobility, and chemical stability of A/B-site co-doped BaHfO3 using density functional theory calculations coupled with statistical thermodynamics. Specifically, I have calculated defect formation energy in charged supercells, finite temperature vibrational energy via phonon calculations in the harmonic approximation, proton migration energy via transition state theory, and defect-defect interactions via cluster-expansion method. A wide range of relevant properties are predicted, including the degree of hydration governed by hydration Gibbs free energy, proton diffusion coefficient derived from proton migration barrier search, and defect-defect interactions using cluster expansion method. These properties are sensitive to the type and amount of chemical dopants in the lattice, including Li, Na, K, Rb, and Cs on A-site and Sc, Y, La, Gd, Lu, Al, Ga, and In on B-site. The mismatch in the size of the dopant and the host ion induces local strain or elastic interactions. However, the electrostatic interactions between them are much less dependent on the ionic radius of dopant ions. Accordingly, the dependence of the dopant-proton binding energy on ionic radius of dopant has a “volcano” shape. In addition, the electronegativity of dopant ions also affect the affinity of acceptor-type dopants with donor-type protons. Hydration is promoted by both the A-site and the B-site dopants, although the effect of the latter is less pronounced. In general, a “trade-off” relation between proton concentration and mobility is observed in all cases, regardless of the ionic radius or the lattice site (A- or B-site) of the dopants. Defects play an important role in ionic transport and in enhancing catalytic activities for chemical and energy transformation processes. Thus, it is crucial to understand how to effectively enhance ionic transport by rationally design preferred defect structures, including 0D (point defects such as vacancies), 1D (dislocation), and 2D (grain boundary) defects. For example, local ion segregation may result in a space charge region, leading to accumulation of mobile charge carriers or improved mobility near those 1D/2D defects. The effect of the space charge layer, strain near 1D/2D defects, as well as collective defect-defect interactions pose an extreme challenge for both experiments and computations. In this study, the effect of an edge dislocation in Y:BaZrO3 on oxygen ion transport is evaluated. To probe the ion mobility, a reactive molecular dynamics simulation based on ReaxFF is utilized to simulate the super-large Y:BaZrO3 supercell with two edge dislocations. Radial distribution functions and thermal/chemical expansion coefficients are used to benchmark the local and global structure properties, and mean-square displacements are used to calculate diffusivity and conductivity. Dislocation is found to lower the activation energy of ionic transport, possibly because of distinct oxygen cage structures locally at the dislocation core. However, optimal Y% for oxygen ion conductivity is shifted to higher levels with increasing temperature. This could be due to the weakening of Y’s electrostatic “trapping effect”. Besides materials chemistry and microstructural features, the mechanical strain is another factor affecting ionic properties. Ceria (or CeO2) is a prototypical ionic material for catalyst and electrolyte applications. Chemo-mechanical coupling in ceria significantly affect the bulk defect properties of ceria. In this study, the effect of chemo-mechanical coupling is extended from the bulk to the (111) surface of ceria. There have been extensive theoretical and experimental research on the configurations of vacancies and polarons on the (111) surface, the dominantly exposed surface, which is crucial to surface catalytic activity. It was reported that surface oxygen vacancy on ceria’s (111) surface is not necessarily the most stable vacancy; however, the sub-surface vacancy could be. Similarly, polarons are not necessarily at the 1st-nearest-neighbor (1NN) of the corresponding vacancy either; they could be at the 2nd-nearest-neighbor (2NN). All those counter-intuitive phenomena were unveiled and validated both theoretically and experimentally. Inspired by previous research, I have identified a unique way of tuning defect configurations by applying tensile and compressive epitaxial strain on (111) slab. Across the magnitude of the applied strain from -5% compression to +5% tension, stability relationships of the surface vs. the sub-surface vacancy, the 1NN vs. the 2NN polaron, and the vacancy monomer vs. the dimer are surprisingly reversed. Elastic, electrostatic and electronic excitation energies are found to be dependent on defect-configuration. This gives us a new perspective to interpret the various vacancy patterns observed on (111) surface of the prepared ceria samples.Ph.D

OSCAR. A Noise Injection Framework for Testing Concurrent Software

“Moore’s Law” is a well-known observable phenomenon in computer science that describes a visible yearly pattern in processor’s die increase. Even though it has held true for the last 57 years, thermal limitations on how much a processor’s core frequencies can be increased, have led to physical limitations to their performance scaling. The industry has since then shifted towards multicore architectures, which offer much better and scalable performance, while in turn forcing programmers to adopt the concurrent programming paradigm when designing new software, if they wish to make use of this added performance. The use of this paradigm comes with the unfortunate downside of the sudden appearance of a plethora of additional errors in their programs, stemming directly from their (poor) use of concurrency techniques. Furthermore, these concurrent programs themselves are notoriously hard to design and to verify their correctness, with researchers continuously developing new, more effective and effi- cient methods of doing so. Noise injection, the theme of this dissertation, is one such method. It relies on the “probe effect” — the observable shift in the behaviour of concurrent programs upon the introduction of noise into their routines. The abandonment of ConTest, a popular proprietary and closed-source noise injection framework, for testing concurrent software written using the Java programming language, has left a void in the availability of noise injection frameworks for this programming language. To mitigate this void, this dissertation proposes OSCAR — a novel open-source noise injection framework for the Java programming language, relying on static bytecode instrumentation for injecting noise. OSCAR will provide a free and well-documented noise injection tool for research, pedagogical and industry usage. Additionally, we propose a novel taxonomy for categorizing new and existing noise injection heuristics, together with a new method for generating and analysing concurrent software traces, based on string comparison metrics. After noising programs from the IBM Concurrent Benchmark with different heuristics, we observed that OSCAR is highly effective in increasing the coverage of the interleaving space, and that the different heuristics provide diverse trade-offs on the cost and benefit (time/coverage) of the noise injection process.Resumo A “Lei de Moore” é um fenómeno, bem conhecido na área das ciências da computação, que descreve um padrão evidente no aumento anual da densidade de transístores num processador. Mesmo mantendo-se válido nos últimos 57 anos, o aumento do desempenho dos processadores continua garrotado pelas limitações térmicas inerentes `a subida da sua frequência de funciona- mento. Desde então, a industria transitou para arquiteturas multi núcleo, com significativamente melhor e mais escalável desempenho, mas obrigando os programadores a adotar o paradigma de programação concorrente ao desenhar os seus novos programas, para poderem aproveitar o desempenho adicional que advém do seu uso. O uso deste paradigma, no entanto, traz consigo, por consequência, a introdução de uma panóplia de novos erros nos programas, decorrentes diretamente da utilização (inadequada) de técnicas de programação concorrente. Adicionalmente, estes programas concorrentes são conhecidos por serem consideravelmente mais difíceis de desenhar e de validar, quanto ao seu correto funcionamento, incentivando investi- gadores ao desenvolvimento de novos métodos mais eficientes e eficazes de o fazerem. A injeção de ruído, o tema principal desta dissertação, é um destes métodos. Esta baseia-se no “efeito sonda” (do inglês “probe effect”) — caracterizado por uma mudança de comportamento observável em programas concorrentes, ao terem ruído introduzido nas suas rotinas. Com o abandono do Con- Test, uma framework popular, proprietária e de código fechado, de análise dinâmica de programas concorrentes através de injecção de ruído, escritos com recurso `a linguagem de programação Java, viu-se surgir um vazio na oferta de framework de injeção de ruído, para esta mesma linguagem. Para mitigar este vazio, esta dissertação propõe o OSCAR — uma nova framework de injeção de ruído, de código-aberto, para a linguagem de programação Java, que utiliza manipulação estática de bytecode para realizar a introdução de ruído. O OSCAR pretende oferecer uma ferramenta livre e bem documentada de injeção de ruído para fins de investigação, pedagógicos ou até para a indústria. Adicionalmente, a dissertação propõe uma nova taxonomia para categorizar os dife- rentes tipos de heurísticas de injecção de ruídos novos e existentes, juntamente com um método para gerar e analisar traces de programas concorrentes, com base em métricas de comparação de strings. Após inserir ruído em programas do IBM Concurrent Benchmark, com diversas heurísticas, ob- servámos que o OSCAR consegue aumentar significativamente a dimensão da cobertura do espaço de estados de programas concorrentes. Adicionalmente, verificou-se que diferentes heurísticas produzem um leque variado de prós e contras, especialmente em termos de eficácia versus eficiência

Catalog 2005-06

https://openspace.dmacc.edu/catalogs/1027/thumbnail.jp