345 research outputs found

    MxTasks: a novel processing model to support data processing on modern hardware

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    The hardware landscape has changed rapidly in recent years. Modern hardware in today's servers is characterized by many CPU cores, multiple sockets, and vast amounts of main memory structured in NUMA hierarchies. In order to benefit from these highly parallel systems, the software has to adapt and actively engage with newly available features. However, the processing models forming the foundation for many performance-oriented applications have remained essentially unchanged. Threads, which serve as the central processing abstractions, can be considered a "black box" that hardly allows any transparency between the application and the system underneath. On the one hand, applications are aware of the knowledge that could assist the system in optimizing the execution, such as accessed data objects and access patterns. On the other hand, the limited opportunities for information exchange cause operating systems to make assumptions about the applications' intentions to optimize their execution, e.g., for local data access. Applications, on the contrary, implement optimizations tailored to specific situations, such as sophisticated synchronization mechanisms and hardware-conscious data structures. This work presents MxTasking, a task-based runtime environment that assists the design of data structures and applications for contemporary hardware. MxTasking rethinks the interfaces between performance-oriented applications and the execution substrate, streamlining the information exchange between both layers. By breaking patterns of processing models designed with past generations of hardware in mind, MxTasking creates novel opportunities to manage resources in a hardware- and application-conscious way. Accordingly, we question the granularity of "conventional" threads and show that fine-granular MxTasks are a viable abstraction unit for characterizing and optimizing the execution in a general way. Using various demonstrators in the context of database management systems, we illustrate the practical benefits and explore how challenges like memory access latencies and error-prone synchronization of concurrency can be addressed straightforwardly and effectively

    Low-latency query compilation

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    Query compilation is a processing technique that achieves very high processing speeds but has the disadvantage of introducing additional compilation latencies. These latencies cause an overhead that is relatively high for short-running and high-complexity queries. In this work, we present Flounder IR and ReSQL, our new approach to query compilation. Instead of using a general purpose intermediate representation (e.g., LLVM IR) during compilation, ReSQL uses Flounder IR, which is specifically designed for database processing. Flounder IR is lightweight and close to machine assembly. This simplifies the translation from IR to machine code, which otherwise is a costly translation step. Despite simple translation, compiled queries still benefit from the high processing speeds of the query compilation technique. We analyze the performance of our approach with micro-benchmarks and with ReSQL, which employs a full translation stack from SQL to machine code. We show reductions in compilation times up to two orders of magnitude over LLVM and show improvements in overall execution time for TPC-H queries up to 5.5 × over state-of-the-art systems

    mxkernel: a novel system software stack for data processing on modern hardware

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    Emerging hardware platforms are characterized by large degrees of parallelism, complex memory hierarchies, and increasing hardware heterogeneity. Their theoretical peak data processing performance can only be unleashed if the different pieces of systems software collaborate much more closely and if their traditional dependencies and interfaces are redesigned. We have developed the key concepts and a prototype implementation of a novel system software stack named mxkernel. For MxKernel, efficient large scale data processing capabilities are a primary design goal. To achieve this, heterogeneity and parallelism become first-class citizens and deep memory hierarchies are considered from the very beginning. Instead of a classical “thread” model, mxkernel provides a simpler control flow abstraction: mxtasks model closed units of work, for which mxkernel will guarantee the required execution semantics, such exclusive access to a specific object in memory. They can be a very elegant abstraction also for heterogeneity and resource sharing. Furthermore, mxtasks are annotated with metadata, such as code variants (to support heterogeneity), memory access behavior (to improve cache efficiency and support memory hierarchies), or dependencies between mxtasks (to improve scheduling and avoid synchronization cost). With precisely the required metadata available, mxkernel can provide a lightweight, yet highly efficient form of resource management, even across applications, operating system, and database. Based on the mxkernel prototype we present preliminary results from this ambitious undertaking. We argue that threads are an ill-suited control flow abstraction for our modern computer architectures and that a task-based execution model is to be favored

    Zur Absorption gepulster ArF-Laserstrahlung in hochtransparenten optischen Materialien

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    Die vorliegende Arbeit beschreibt Experimente und Modellrechnungen zur Absorption gepulster ArF-Laserstrahlung in synthetischem Quarzglas (Typ III) und CaF2. Die direkte Messung der Volumenabsorption erfolgt mit nur einer Probe durch die absolut kalibrierbare LID-Methode (LID-laser induced deflection). Ein Vergleich zwischen beiden untersuchten Materialien zeigt: Während im CaF2 Verunreinigungen (z.B. Natrium) das Absorptions-verhalten bestimmen, wird dieses in synthetischem Quarzglas durch intrinsische Defekte (E´, ODC, SiH) bewirkt

    Charakterisierung der Einflussfaktoren auf SERS-Spektren niedermolekularer Substanzen und medizinisch relevante Anwendungen des LOC-SERS-Systems

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    Die Kombination von oberflächenverstärkter Raman-Spektroskopie (SERS) und einem mikrofluidischen Lab-on-a-chip (LOC)-System ist ein vielversprechender analytischer Ansatz für die medizinische Diagnostik. Die SERS-Spektren enthalten molekularspezifische Informationen und ermöglichen somit eine Detektion molekularer Systeme im submikromolaren Bereich. Die LOC-SERS-Methode ermöglicht eine hohe Durchsatzrate von Einzelproben unter geringen Aufkommen von Probenvolumina. Weiterhin ist die Implementierung von Modulen zur Probenvorbehandlung mit geringem technischem Aufwand realisierbar. Im Rahmen dieser Arbeit sollen die vielfältigen Möglichkeiten des mikrofluidischen SERS-Systems aufgezeigt werden. Durch die Verwendung des LOC-SERS-Systems wird die Bestimmung exakter Messbedingungen und eine hohe Reproduzierbarkeit gewährleistet. In einer Grundlagenstudie werden in dieser Arbeit die Einflüsse auf SERS-Spektren untersucht. Hierbei werden Pyridin und monosubstituierte Pyridinderivate als Analyten verwendet. Es wird gezeigt, dass für eine akkurate Bandenzuordnung die Inklusion quantenchemischer Methoden unerlässlich ist. Es wird demonstriert, dass anhand von LOC-SERS-Datensätzen quantitative Analysen in komplexen Medien durchgeführt werden können. Der Antimetabolit Methotrexat (MTX) wird in wässriger Lösung sowie in artifiziellem Blutplasma semi-quantitativ detektiert, unterschiedliche Konzentrationen von MTX in realem Blutplasma können eindeutig unterschieden werden. Des Weiteren werden Pathogene mittels chemometrischer Methoden anhand der SERS-Spektren von Markermolekülen identifiziert. Im Fokus der Arbeit steht dabei die Detektion niedermolekularer Substanzen in komplexen Medien, wie Blutplasma und Bakteriensuspension sowie die Identifizierung pathogener Mykobakterien

    Towards self-assembled metamaterials

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    How far can we push chemical self-assembly? This is one of the 25 biggest questions science is facing over the next quarter century, as reported by the Science journal in 2005. The idea of self-assembly is to fabricate synthetic structures or materials from the bottom-up. Up to date a huge class of distinct structures was successfully demonstrated to be fabricated by self-assembly. One important scientific area that exerts the ideas of self-assembly arose from the fusion of the fields of colloidal nanochemistry and nanooptics. There, the focus is on the fabrication of bottom-up nanophotonic structures with a tailored optical response. Very interesting are self-assembled metamaterials (MMs). They promise to widen the possibilities on how to control the propagation of light to an extraordinary degree. Concerning self-assembled MMs the precise spatial arrangement of its unit cells across larger dimensions is not possible in most cases; leading essentially to amorphous structures. Such self-assembled MMs require novel analytical means to describe their optical properties and innovative designs of functional elements that possess a desired near- and far-field response. The first goal of this thesis is the introduction and development of a feasible theoretical description of amorphous MMs. Once the theory is established the second goal is on experimental realizations of self-assembled MMs. Therefore, the focus of this thesis is on self-assembled MMs and the question on how far they can be pushed to obtain artificial materials with an extraordinary optical response
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