Institutes
Refine
Year of publication
Document Type
- Doctoral Thesis (91)
- Article (59)
- Bachelor Thesis (18)
- Book (13)
- Master's Thesis (10)
- Conference Proceeding (4)
- Contribution to a Periodical (4)
- Habilitation (2)
- Preprint (2)
- Diploma Thesis (1)
Has Fulltext
- yes (204)
Is part of the Bibliography
- no (204)
Keywords
- Machine Learning (5)
- NLP (5)
- ALICE (3)
- Annotation (3)
- Machine learning (3)
- Text2Scene (3)
- TextAnnotator (3)
- Virtual Reality (3)
- mathematics education (3)
- Artificial intelligence (2)
Institute
In this thesis we introduce the imaginary projection of (multivariate) polynomials as the projection of their variety onto its imaginary part, I(f) = { Im(z_1, ... , z_n) : f(z_1, ... , z_n) = 0 }. This induces a geometric viewpoint to stability, since a polynomial f is stable if and only if its imaginary projection does not intersect the positive orthant. Accordingly, the thesis is mainly motivated by the theory of stable polynomials.
Interested in the number and structure of components of the complement of imaginary projections, we show as a key result that there are only finitely many components which are all convex. This offers a connection to the theory of amoebas and coamoebas as well as to the theory of hyperbolic polynomials.
For hyperbolic polynomials, we show that hyperbolicity cones coincide with components of the complement of imaginary projections, which provides a strong structural relationship between these two sets. Based on this, we prove a tight upper bound for the number of hyperbolicity cones and, respectively, for the number of components of the complement in the case of homogeneous polynomials. Beside this, we investigate various aspects of imaginary projections and compute imaginary projections of several classes explicitly.
Finally, we initiate the study of a conic generalization of stability by considering polynomials whose roots have no imaginary part in the interior of a given real, n-dimensional, proper cone K. This appears to be very natural, since many statements known for univariate and multivariate stable polynomials can be transferred to the conic situation, like the Hermite-Biehler Theorem and the Hermite-Kakeya-Obreschkoff Theorem. When considering K to be the cone of positive semidefinite matrices, we prove a criterion for conic stability of determinantal polynomials.
As an integral part of ALICE, the dedicated heavy ion experiment at CERN’s Large Hadron Collider, the Transition Radiation Detector (TRD) contributes to the experiment’s tracking, triggering and particle identification. Central element in the TRD’s processing chain is its trigger and readout processor, the Global Tracking Unit (GTU). The GTU implements fast triggers on various signatures, which rely on the reconstruction of up to 20 000 particle track segments to global tracks, and performs the buffering and processing of event raw data as part of a complex detector readout tree.
The high data rates the system has to handle and its dual use as trigger and readout processor with shared resources and interwoven processing paths require the GTU to be a unique, high-performance parallel processing system. To achieve high data taking efficiency, all elements of the GTU are optimized for high running stability and low dead time.
The solutions presented in this thesis for the handling of readout data in the GTU, from the initial reception to the final assembly and transmission to the High-Level Trigger computer farm, address all these aspects. The presented concepts employ multi-event buffering, in-stream data processing, extensive embedded diagnostics, and advanced features of modern FPGAs to build a robust high-performance system that can conduct the high- bandwidth readout of the TRD with maximum stability and minimized dead time. The work summarized here not only includes the complete process from the conceptual layout of the multi-event data handling and segment control, but also its implementation, simulation, verification, operation and commissioning. It also covers the system upgrade for the second data taking period and presents an analysis of the actual system performance.
The presented design of the GTU’s input stage, which is comprised of 90 FPGA-based nodes, is built to support multi-event buffering for the data received from the 18 TRD supermodules on 1080 optical links at the full sender aggregate net bandwidth of 2.16 Tbit/s. With careful design of the control logic and the overall data path, the readout on the 18 concentrator nodes of the supermodule stage can utilize an effective aggregate output bandwidth of initially 3.33 GiB/s, and, after the successful readout bandwidth upgrade, 6.50 GiB/s via 18 optical links. The high possible readout link utilization of more than 99 % and the intermediate buffering of events on the GTU helps to keep the dead time associated with the local event building and readout typically below 10%. The GTU has been used for production data taking since start-up of the experiment and ever since performs the event buffering, local event building and readout for the TRD in a correct, efficient and highly dependable fashion.
Eine 1-1-Korrespondenz zwischen einer Klasse von Leftist-Bäumen und erweiterten t-nären Bäumen
(2006)
Leftist-Bäume sind eine Teilmenge der geordneten Bäume mit der Eigenschaft, daß der [kürzeste] Weg von jedem inneren Knoten zu einem Blatt des Teilbaums mit diesem Knoten als Wurzel immer über den am weitesten links stehenden Sohn dieses Knotens verläuft.
In der vorliegenden Arbeit wird eine 1-1-Korrespondenz zwischen erweiterten t-nären Bäumen und der Klasse der Leftist-Bäumen mit erlaubten Knotengraden 0, t, 2t-1, ... 1+t(t-1) präsentiert. Diese 1-1-Korrespondenz verallgemeinert ein Ergebnis von R. Kemp.
Embedding spanning structures into the random graph G(n,p) is a well-studied problem in random graph theory, but when one turns to the random r-uniform hypergraph H(r)(n,p) much less is known. In this thesis we will examine this topic from different perspectives, providing insights into various aspects of the theory of random graphs. Our results cover the determination of existence thresholds in two models, as well as an algorithmic approach. For the embeddings, we work with random and pseudorandom structures.
Together with Person we first notice that a general result of Riordan can be adapted from random graphs to hypergraphs and provide sufficient conditions for when H(r)(n,p) contains a given spanning structure asymptotically almost surely. As applications, we discuss several spanning structures such as cubes, lattices, spheres, and Hamilton cycles in hypergraphs.
Moreover, we study universality, i.e. when does an r-uniform hypergraph contain every hypergraph on n vertices with maximum vertex degree bounded by [delta]? For H(r)(n,p), it is shown with Person that this holds for p = w(ln n/n)1/[delta]) asymptotically almost surely by combining approaches taken by Dellamonica, Kohayakawa, Rödl, and Ruciński, of Ferber, Nenadov, and Peter, and of Kim and Lee.
Any hypergraph that is universal for the family of bounded degree r-uniform hypergraphs has to contain [omega](nr-r/[delta]) edges. With Hetterich and Person we exploit constructions of Alon and Capalbo to obtain universal r-uniform hypergraphs with the optimal number of edges O(nr-r/[delta]) when r is even, r | [delta], or [delta] = 2. Furthermore, we generalise the result of Alon and Asodi about optimal universal graphs for the family of graphs with at most m edges and no isolated vertices to hypergraphs.
In an r-uniform hypergraph on n vertices a tight Hamilton cycle consists of n edges such that there exists a cyclic ordering of the vertices where the edges correspond to consecutive segments of r vertices. In collaboration with Allen, Koch, and Person we provide a first deterministic polynomial time algorithm, which finds asymptotically almost surely tight Hamilton cycles in random r-uniform hypergraphs with edge probability at least C log3 n/n. This result partially answers a question of Nenadov and Skorić and of Dudek and Frieze who proved that tight Hamilton cycles exist already for p = w(1/n) for r = 3 and p [größer/gleich] (e + o(1))/n for r [größer/gleich] 4 using a second moment argument. Moreover our algorithm is superior to previous results of Allen, Böttcher, Kohayakawa, and Person and Nenadov and Skorić.
Lastly, we study the model of randomly perturbed dense graphs introduced by Bohman, Frieze and Martin, that is, the union of any n-vertex graph G[alpha] with minimum degree at least [alpha]n and G(n,p). For any fixed [alpha] > 0, and p = w(n-2/([delta]+1)), we show with Böttcher, Montgomery, and Person that G[alpha] UG(n,p) almost surely contains any single spanning graph with maximum degree [delta], where [delta] [größer/gleich] 5. As in previous results concerning this model, the bound used for p is lower by a log-term in comparison to the conjectured threshold for the general appearance of such subgraphs in G(n,p) alone. The new techniques we introduce also give simpler proofs of related results in the literature on trees and factors.
Measuring information processing in neural data: The application of transfer entropy in neuroscience
(2017)
It is a common notion in neuroscience research that the brain and neural systems in general "perform computations" to generate their complex, everyday behavior (Schnitzer, 2002). Understanding these computations is thus an important step in understanding neural systems as a whole (Carandini, 2012;Clark, 2013; Schnitzer, 2002; de-Wit, 2016). It has been proposed that one way to analyze these computations is by quantifying basic information processing operations necessary for computation, namely the transfer, storage, and modification of information (Langton, 1990; Mitchell, 2011; Mitchell, 1993;Wibral, 2015). A framework for the analysis of these operations has been emerging (Lizier2010thesis), using measures from information theory (Shannon, 1948) to analyze computation in arbitrary information processing systems (e.g., Lizier, 2012b). Of these measures transfer entropy (TE) (Schreiber2000), a measure of information transfer, is the most widely used in neuroscience today (e.g., Vicente, 2011; Wibral, 2011; Gourevitch, 2007; Vakorin, 2010; Besserve, 2010; Lizier, 2011; Richter, 2016; Huang, 2015; Rivolta, 2015; Roux, 2013). Yet, despite this popularity, open theoretical and practical problems in the application of TE remain (e.g., Vicente, 2011; Wibral, 2014a). The present work addresses some of the most prominent of these methodological problems in three studies.
The first study presents an efficient implementation for the estimation of TE from non-stationary data. The statistical properties of non-stationary data are not invariant over time such that TE can not be easily estimated from these observations. Instead, necessary observations can be collected over an ensemble of data, i.e., observations of physical or temporal replications of the same process (Gomez-Herrero, 2010). The latter approach is computationally more demanding than the estimation from observations over time. The present study demonstrates how to handles this increased computational demand by presenting a highly-parallel implementation of the estimator using graphics processing units.
The second study addresses the problem of estimating bivariate TE from multivariate data. Neuroscience research often investigates interactions between more than two (sub-)systems. It is common to analyze these interactions by iteratively estimating TE between pairs of variables, because a fully multivariate approach to TE-estimation is computationally intractable (Lizier, 2012a; Das, 2008; Welch, 1982). Yet, the estimation of bivariate TE from multivariate data may yield spurious, false-positive results (Lizier, 2012a;Kaminski, 2001; Blinowska, 2004). The present study proposes that such spurious links can be identified by characteristic coupling-motifs and the timings of their information transfer delays in networks of bivariate TE-estimates. The study presents a graph-algorithm that detects these coupling motifs and marks potentially spurious links. The algorithm thus partially corrects for spurious results due to multivariate effects and yields a more conservative approximation of the true network of multivariate information transfer.
The third study investigates the TE between pre-frontal and primary visual cortical areas of two ferrets under different levels of anesthesia. Additionally, the study investigates local information processing in source and target of the TE by estimating information storage (Lizier, 2012) and signal entropy. Results of this study indicate an alternative explanation for the commonly observed reduction in TE under anesthesia (Imas, 2005; Ku, 2011; Lee, 2013; Jordan, 2013; Untergehrer, 2014), which is often explained by changes in the underlying coupling between areas. Instead, the present study proposes that reduced TE may be due to a reduction in information generation measured by signal entropy in the source of TE. The study thus demonstrates how interpreting changes in TE as evidence for changes in causal coupling may lead to erroneous conclusions. The study further discusses current bast-practice in the estimation of TE, namely the use of state-of-the-art estimators over approximative methods and the use of optimization procedures for estimation parameters over the use of ad-hoc choices. It is demonstrated how not following this best-practice may lead to over- or under-estimation of TE or failure to detect TE altogether.
In summary, the present work proposes an implementation for the efficient estimation of TE from non-stationary data, it presents a correction for spurious effects in bivariate TE-estimation from multivariate data, and it presents current best-practice in the estimation and interpretation of TE. Taken together, the work presents solutions to some of the most pressing problems of the estimation of TE in neuroscience, improving the robust estimation of TE as a measure of information transfer in neural systems.
The ALICE High-Level-Trigger (HLT) is a large scale computing farm designed and constructed for the purpose of the realtime reconstruction of particle interactions (events) inside the ALICE detector. The reconstruction of such events is based on the raw data produced in collisions inside the ALICE at the Large Hadron Collider. The online reconstruction in the HLT allows the triggering on certain event topologies and a significant data reduction by applying compression algorithms. Moreover, it enables a real-time verification of the quality of the data.
To receive the raw data from the various sub-detectors of ALICE, the HLT is equipped with 226 custom built FPGA-based PCI-X cards, the H-RORCs. The H-RORC interfaces the detector readout electronics to the nodes of the HLT farm. In addition to the transfer of raw data, 108 H-RORCs host 216 Fast-Cluster-Finder (FCF) processors for the Time-Projection-Chamber (TPC). The TPC is the main tracking detector of ALICE and contributes with up to 16 GB/s to over 90% of the overall data volume. The FCF processor implements the first of two steps in the data reconstruction of the TPC. It calculates the space points and their properties from charge clouds (clusters) created by charged particles traversing the TPCs gas volume. Those space points are not only the base for the tracking algorithm, but also allow for a Huffman-based data compression, which reduces the data volume by a factor of 4 to 6.
The FCF processor is designed to cope with any incoming data rate up to the maximum bandwidth of the incoming optical link (160 MB/s) without creating back-pressure to the detectors readout electronics. A performance comparison with the software implementation of the algorithm shows a speedup factor of about 20 compared with one AMD Opteron 6172 Core @ 2.1 GHz, the CPU type used in the HLT during the LHC Run1 campaign. Comparison with an Intel E5-2690 Core @ 3.0 GHz, the CPU type used by the HLT for the LHC Run2 campaign, results in a speedup factor of 8.5. In total numbers, the 216 FCF processors provide the computing performance of 4255 AMD Opteron cores or 2203 Intel cores of the previously mentioned type. The performance of the reconstruction with respect to the physics analysis is equivalent or better than the official ALICE Offline clusterizer. Therefore, ALICE data taking was switched in 2011 to FCF cluster recording and compression only, discarding the raw data from the TPC. Due to the capability to compress the clusters, the recorded data volume could be increased by a factor of 4 to 6.
For the LHC Run3 campaign, starting in 2020, the FCF builds the foundation of the ALICE data taking and processing strategy. The raw data volume (before processing) of the upgraded TPC will exceed 3 TB/s. As a consequence, online processing of the raw data and compression of the results before it enters the online computing farms is an essential and crucial part of the computing model.
Within the scope of this thesis, the H-RORC card and the FCF processor were developed and built from scratch. It covers the conceptual design, the optimisation and implementation, as well as the verification. It is completed by performance benchmarks and experiences from real data taking.
Urn models are simple examples for random growth processes that involve various competing types. In the study of these schemes, one is generally interested in the impact of the specific form of interaction on the allocation of elements to the types. Depending on their reciprocal action, effects of cancellation and self-reinforcement become apparent in the long run of the system. For some urn models, the influencing is of a smoothing nature and the asymptotic allocation to the types is close to being a result of independent and identically distributed growth events. On the contrary, for others, almost sure random tendencies or logarithmically periodic terms emerge in the second growth order. The present thesis is devoted to the derivation of central limit theorems in the latter case. For urns of this kind, we use a "non-classical" normalisation to derive asymptotic joint normality of the types. This normalisation takes random tendencies and phases into account and consequently involves random centering and, also, possibly random scaling.
Biological ageing is a degenerative and irreversible process, ultimately leading to death of the organism. The process is complex and under the control of genetic, environmental and stochastic traits. Although many theories have been established during the last decades, none of these are able to fully describe the complex mechanisms, which lead to ageing. Generally, biological processes and environmental factors lead to molecular damage and an accumulation of impaired cellular components. In contrast, counteracting surveillance systems are effective, including repair, remodelling and degradation of damaged or impaired components, respectively. Nevertheless, at some point these systems are no longer effective, either because the increasing amount of molecular damages can not longer be removed efficiently or because the repairing and removing mechanisms themselves become affected by impairing effects. The organism finally declines and dies. To investigate and to understand these counteracting mechanisms and the complex interplay of decline and maintenance, holistic and systems biological investigations are required. Hence, the processes which lead to ageing in the fungal model organism Podospora anserina, had been analysed using different advanced bioinformatics methods. In contrast to many other ageing models, P. anserina exhibits a short lifespan, a less biochemical complexity and it provides a good accessibility for genetic manipulations.
To achieve a general overview on the different biochemical processes, which are affected during ageing in P. anserina, an initial comprehensive investigation was applied, which aimed to reveal genes significantly regulated and expressed in an age-dependent manner. This investigation was based on an age-dependent transcriptome analysis. Sophisticated and comprehensive analyses revealed different age-related pathways and indicated that especially autophagy may play a crucial role during ageing. For example, it was found that the expression of autophagy-associated genes increases in the course of ageing.
Subsequently, to investigate and to characterise the autophagy pathway, its associated single components and their interactions, Path2PPI, a new bioinformatics approach, was developed. Path2PPI enables the prediction of protein-protein interaction networks of particular pathways by means of a homology comparison approach and was applied to construct the protein-protein interaction network of autophagy in P. anserina.
The predicted network was extended by experimental data, comprising the transcriptome data as well as newly generated protein-protein interaction data achieved from a yeast two-hybrid analysis. Using different mathematical and statistical methods the topological properties of the constructed network had been compared with those of randomly generated networks to approve its biological significance. In addition, based on this topological and functional analysis, the most important proteins were determined and functional modules were identified, which correspond to the different sub-pathways of autophagy. Due to the integrated transcriptome data the autophagy network could be linked to the ageing process. For example, different proteins had been identified, which genes are continuously up- or down-regulated during ageing and it was shown for the first time that autophagy-associated genes are significantly often co-expressed during ageing.
The presented biological network provides a systems biological view on autophagy and enables further studies, which aim to analyse the relationship of autophagy and ageing. Furthermore, it allows the investigation of potential methods for intervention into the ageing process and to extend the healthy lifespan of P. anserina as well as of other eukaryotic organisms, in particular humans.
For the class of balanced, irreducible Pólya urn schemes with two colours, say black and white, limit theorems for the number of black balls after n steps are known. Depending on the ratio of the eigenvalues of the replacement matrix, two regimes of limit laws occur: almost sure convergence to a non-degenerate random variable whose distribution depends on the initial composition of the urn and that is known to be not normally distributed and weak convergence to the normal distribution. In this thesis, upper bounds on the rates of convergence in both the non-normal limit case and the normal limit case are given.
Recently, Aumüller and Dietzfelbinger proposed a version of a dual-pivot Quicksort, called "Count", which is optimal among dual-pivot versions with respect to the average number of key comparisons required. In this master's thesis we provide further probabilistic analysis of "Count". We derive an exact formula for the average number of swaps needed by "Count" as well as an asymptotic formula for the variance of the number of swaps and a limit law. Also for the number of key comparisons the asymptotic variance and a limit law are identified. We also consider both complexity measures jointly and find their asymptotic correlation.
The future heavy-ion experiment CBM (FAIR/GSI, Darmstadt, Germany) will focus on the measurements of very rare probes, which require the experiment to operate under extreme interaction rates of up to 10 MHz. Due to high multiplicity of charged particles in heavy-ion collisions, this will lead to the data rates of up to 1 TB/s. In order to meet the modern achievable archival rate, this data ow has to be reduced online by more than two orders of magnitude.
The rare observables are featured with complicated trigger signatures and require full event topology reconstruction to be performed online. The huge data rates together with the absence of simple hardware triggers make traditional latency limited trigger architectures typical for conventional experiments inapplicable for the case of CBM. Instead, CBM will employ a novel data acquisition concept with autonomous, self-triggered front-end electronics.
While in conventional experiments with event-by-event processing the association of detector hits with corresponding physical event is known a priori, it is not true for the CBM experiment, where the reconstruction algorithms should be modified in order to process non-event-associated data. At the highest interaction rates the time difference between hits belonging to the same collision will be larger than the average time difference between two consecutive collisions. Thus, events will overlap in time. Due to a possible overlap of events one needs to analyze time-slices rather than isolated events.
The time-stamped data will be shipped and collected into a readout buffer in a form of a time-slice of a certain length. The time-slice data will be delivered to a large computer farm, where the archival decision will be obtained after performing online reconstruction. In this case association of hit information with physical events must be performed in software and requires full online event reconstruction not only in space, but also in time, so-called 4-dimensional (4D) track reconstruction.
Within the scope of this work the 4D track finder algorithm for online reconstruction has been developed. The 4D CA track finder is able to reproduce performance and speed of the traditional event-based algorithm. The 4D CA track finder is both vectorized (using SIMD instructions) and parallelized (between CPU cores). The algorithm shows strong scalability on many-core systems. The speed-up factor of 10.1 has been achieved on a CPU with 10 hyper-threaded physical cores.
The 4D CA track finder algorithm is ready for the time-slice-based reconstruction in the CBM experiment.
Modern mobile devices offer a great variety of data that can be recorded. This broad range of information offers the possibility to tailor applications more to the needs of a user. Several context information can be collected, like e.g. information about position or movement. Besides integrated sensors, a broad range of additional sensors are available which can be connected to a mobile device. These additional sensors offer for example the possibility to measure physiological signals of a user.The human body offers a broad range of different signals. These signals have been used in several examples to conclude on the state of a user. The different signals allow to get a deeper insight into emotional or mental state of a user. Electrodermal activity gives feedback about the current arousal level of a user. Heart rate and heart rate variability can give an estimation about valence and mental load of a user. Several models exist to conclude from information like valence and arousal on different emotional states. Russell defined a two dimensional model, using valence and arousal to define affective states. Yerkes and Dodson developed a curve that expresses the relationship between arousal and performance of a user. Different examples exist, that use physiological signals to determine the user state for tailoring and adapting of applications. At the time of this work most of these examples did not address the usage of physiological signals for user state estimation in mobile applications and in mobile scenarios. Mobile scenarios lead to several challenges that need to be addressed. Influencing factors on physiological signals, like e.g. movement have to be controlled. Furthermore a user might be interrupted and influenced by environmental aspects. The combination of physiological data and context information might improve the interpretation of user state in mobile scenarios. In this work, we present a model that addresses the challenges of usage in mobile scenarios to offer an estimation of user state to mobile applications. To address a broad range of mobile applications, affective and cognitive state are provided as output. As input heart rate and electrodermal activity are used, as well as context information about movement and performance. Electrodermal activity is measured by a simple sensor that can be worn as a wristband. Heart rate is measured by a chest strap as used in sports. The input channels are transformed to affective and cognitive state based on a fuzzy rule based approach. With help of fuzzy logic, uncertainty can be expressed and the data continuously being processed. At the start, input channels are fuzzified by defined functions. After a that, a first fuzzy rule set transforms the input signals into values for valence, arousal and mental load. In a second step, these values and context information are transformed with another fuzzy rule set to values for affective and cognitive state. Affective state is based on the model of Russell, where valence and arousal are used to determine different emotional states. The output of the model are eight different affective states (alarmed, excited, happy, relaxed, tired, bored, sad and frustrated), which can have a high, medium, low or very low value as output. Cognitive state is determined based on mental load and context information about performance and movement. The output value can be very high, high, medium or low. The model was implemented as background service for Android devices. Different applications have been used for evaluation of the model. The model has been integrated in a multiplayer space shooter game, called ”Zone of Impulse”, which mainly benefits from the affective state. Cognitive state is more addressed in applications like a simple vocable trainer, which adapts difficulty based on user state. A study to evaluate different aspects of the model has been conducted. The study was designed to investigate the suitability of the model for mobile scenarios. The game ”zone of impulse” and the vocable trainer have been investigated in different configurations. Versions with integrated model have been compared to version of the applications without model, as well as versions of the model without context information. In total 41 participants took part in the study. A part of the participants had to do the tasks of the study in a mobile scenario, walking around several streets. The remaining participants had to do the tasks in a controlled environment in a sitting position. Different aspects were collected with ratings and questionnaires. Overall, participants rated that they did not feel impaired by the sensors they had to wear. The results showed, that the combination of physiological data and context information had an advantage against versions without context information in part of the ratings. A comparison between versions with and without model showed, that the subjective mental load ratings were significantly better for the version with model. Subjective ratings for aspects like fun, overstrain and support were mixed. When comparing the application versions in indoor and outdoor scenarios, no significant difference could be found, which leads to the assumption that there is no loss of interpretation quality in outdoor scenarios. The results also showed that the model seems to be robust enough to compensate the loss of an input channel, as there was no significant difference between application versions with full integrated model and versions with one channel lost. With the model developed in this work, context information and physiological data were combined to improve user state estimation. Furthermore pitfalls of user state estimation in mobile scenarios are overcome with this combination. However, the model has only been evaluated with a limited amount of applications and situations that mobile scenarios offer.
Data-parallel programming is more important than ever since serial performance is stagnating. All mainstream computing architectures have been and are still enhancing their support for general purpose computing with explicitly data-parallel execution. For CPUs, data-parallel execution is implemented via SIMD instructions and registers. GPU hardware works very similar allowing very efficient parallel processing of wide data streams with a common instruction stream.
These advances in parallel hardware have not been accompanied by the necessary advances in established programming languages. Developers have thus not been enabled to explicitly state the data-parallelism inherent in their algorithms. Some approaches of GPU and CPU vendors have introduced new programming languages, language extensions, or dialects enabling explicit data-parallel programming. However, it is arguable whether the programming models introduced by these approaches deliver the best solution. In addition, some of these approaches have shortcomings from a hardware-specific focus of the language design. There are several programming problems for which the aforementioned language approaches are not expressive and flexible enough.
This thesis presents a solution tailored to the C++ programming language. The concepts and interfaces are presented specifically for C++ but as abstract as possible facilitating adoption by other programming languages as well. The approach builds upon the observation that C++ is very expressive in terms of types. Types communicate intention and semantics to developers as well as compilers. It allows developers to clearly state their intentions and allows compilers to optimize via explicitly defined semantics of the type system.
Since data-parallelism affects data structures and algorithms, it is not sufficient to enhance the language's expressivity in only one area. The definition of types whose operators express data-parallel execution automatically enhances the possibilities for building data structures. This thesis therefore defines low-level, but fully portable, arithmetic and mask types required to build a flexible and portable abstraction for data-parallel programming. On top of these, it presents higher-level abstractions such as fixed-width vectors and masks, abstractions for interfacing with containers of scalar types, and an approach for automated vectorization of structured types.
The Vc library is an implementation of these types. I developed the Vc library for researching data-parallel types and as a solution for explicitly data-parallel programming. This thesis discusses a few example applications using the Vc library showing the real-world relevance of the library. The Vc types enable parallelization of search algorithms and data structures in a way unique to this solution. It shows the importance of using the type system for expressing data-parallelism. Vc has also become an important building block in the high energy physics community. Their reliance on Vc shows that the library and its interfaces were developed to production quality.
In the first part of the thesis, we show that the payment flow of a linear tax on trading gains from a security with a semimartingale price process can be constructed for all càglàd and adapted trading strategies. It is characterized as the unique continuous extension of the tax payments for elementary strategies w.r.t. the convergence "uniformly in probability". In this framework, we prove that under quite mild assumptions dividend payoffs have almost surely a negative effect on investor’s after-tax wealth if the riskless interest rate is always positive. In addition, we give an example for tax-efficient strategies for which the tax payment flow can be computed explicitly.
In the second part of the thesis, we investigate the impact of capital gains taxes on optimal investment decisions in a quite simple model. Namely, we consider a risk neutral investor who owns one risky stock from which she assumes that it has a lower expected return than the riskless bank account and determine the optimal stopping time at which she sells the stock to invest the proceeds in the bank account up to the maturity date. In the case of linear taxes and a positive riskless interest rate, the problem is nontrivial because at the selling time the investor has to realize book profits which triggers tax payments. We derive a boundary that is continuous and increasing in time, and decreasing in the volatility of the stock such that the investor sells the stock at the first time its price is smaller or equal to this boundary.
On development, feasibility, and limits of highly efficient CPU and GPU programs in several fields
(2013)
With processor clock speeds having stagnated, parallel computing architectures have achieved a breakthrough in recent years. Emerging many-core processors like graphics cards run hundreds of threads in parallel and vector instructions are experiencing a revival. Parallel processors with many independent but simple arithmetical logical units fail executing serial tasks efficiently. However, their sheer parallel processing power makes them predestined for parallel applications while the simple construction of their cores makes them unbeatably power efficient. Unfortunately, old programs cannot profit by simple recompilation. Adaptation often requires rethinking and modifying algorithms to make use of parallel execution. Many applications have some serial subroutines which are very hard to parallelize, hence contemporary compute clusters are often homogeneous, offering fast processors for serial tasks and parallel processors for parallel tasks. In order not to waste the available compute power, highly efficient programs are mandatory.
This thesis is about the development of fast algorithms and their implementations on modern CPUs and GPUs, about the maximum achievable efficiency with respect to peak performance and to power consumption respectively, and about feasibility and limits of programs for CPUs, GPUs, and heterogeneous systems. Three totally different applications from distinct fields, which were developed in the extent of this thesis, are presented.
The ALICE experiment at the LHC particle collider at CERN studies heavy-ion collisions at high rates of several hundred Hz, while every collision produces thousands of particles, whose trajectories must be reconstructed. For this purpose, ALICE track reconstruction and ALICE track merging have been adapted for GPUs and deployed on 64 GPU-enabled compute-nodes at CERN.
After a testing phase, the tracker ran in nonstop operation during 2012 providing full real-time track reconstruction. The tracker employs a multithreaded pipeline as well as asynchronous data transfer to ensure continuous GPU utilization and outperforms the fastest available CPUs by about a factor three.
The Linpack benchmark is the standard tool for ranking compute clusters. It solves a dense system of linear equations using primarily matrix multiplication facilitated by a routine called DGEMM. A heterogeneous GPU-enabled version of DGEMM and Linpack has been developed, which can utilize the CAL, CUDA, and OpenCL APIs as backend. Employing this implementation, the LOEWE-CSC cluster ranked place 22 in the November 2010 Top500 list of the fastest supercomputers, and the Sanam cluster achieved the second place in the November 2012 Green500 list of the most power efficient supercomputers. An elaborate lookahead algorithm, a pipeline, and asynchronous data transfer hide the serial CPU-bound tasks of Linpack behind DGEMM execution on the GPU reaching the highest efficiency on GPU-accelerated clusters.
Failure erasure codes enable failure tolerant storage of data and real-time failover, ensuring that in case of a hardware defect servers and even complete data centers remain operational. It is an absolute necessity for present-day computer infrastructure. The mathematical theory behind the codes involves matrix-computations in finite fields, which are not natively supported by modern processors and hence computationally very expensive. This thesis presents a novel scheme for fast encoding matrix generation and demonstrates a fast implementation for the encoding itself, which uses exclusively either integer or logical vector instructions. Depending on the scenario, it is always hitting different hard limits of the hardware: either the maximum attainable memory bandwidth, or the peak instruction throughput, or the PCI Express bandwidth limit when GPUs or FPGAs are used.
The thesis demonstrates that in most cases with respect to the available peak performance, GPU implementations can be as efficient as their CPU counterparts.
With respect to costs or power consumption, they are much more efficient. For this purpose, complex tasks must be split in serial as well as parallel parts and the execution must be pipelined such that the CPU bound tasks are hidden behind GPU execution. Few cases are identified where this is not possible due to PCI Express limitations or not reasonable because practical GPU languages are missing.
Die zentralen Objekte der Dissertation sind Translationsflächen. Dabei handelt es sich um Riemann’sche Flächen, die aus in die euklidische Ebene eingebetteten Polygonen durch Verkleben von parallelen gleichlangen Seiten entstehen. Zwei Translationsflächen sind gleich, wenn es möglich ist, die Polygone durch ”Zerschneiden und mittels Translationen neu Zusammenkleben“ ineinander zu überführen. Die Gruppe GL_2(R) operiert auf der Menge der Translationsflächen via der linearen Abbildungen auf den Polygonen. Der Stabilisator einer Translationsfläche X unter dieser Operation wird die Veech-Gruppe von X genannt und mit SL(X) bezeichnet. Die Veech-Gruppe ist eine diskrete Untergruppe von SL_2(R) und damit eine Fuchs’sche Gruppe.
Fuchs’sche Gruppen werden je nach ihrer Limesmenge in elementare und nicht-elementare Gruppen eingeteilt. Letztere wiederum unterteilt man in Gruppen erster oder zweiter Art. Fuchs’sche Gruppen mit endlichem co-Volumen heißen Gitter und sind genau die endlich erzeugten Gruppen erster Art. Translationsflächen, deren Veech-Gruppe ein Gitter ist, heißen Veech-Flächen und sind von besonderem Interesse, da für sie die Veech Alternative gilt.
Ein feineres Maß für die Größe einer Fuchs’schen Gruppe ist der kritische Exponent. Er ist definiert als das Infimum aller reellen Zahlen, für die die Poincaré Reihe konvergiert und liegt für alle unendlichen Fuchs’schen Gruppen zwischen 0 und 1. Hauptziel der Dissertation ist der Beweis von Theorem 1. Es gibt Translationsflächen, für die der kritische Exponent ihrer Veech-Gruppe echt zwischen 1/2 und 1 liegt.
Der kritische Exponent von elementaren Gruppen ist höchstens 1/2, Translationsflächen mit elementaren Veech-Gruppen sind also als Kandidaten für das Theorem ausgeschlossen. Der kritische Exponent von Gittern ist 1. Also scheiden auch Veech-Flächen für das Theorem aus.
Bis zum Jahr 2003 waren Gitter die einzigen bekannten nicht-elementaren Veech-Gruppen. McMullen klassifizierte die Veech-Flächen vom Geschlecht 2 und zeigte, dass jede solche Fläche, die nur eine Singularität besitzt, in der GL_2(R)-Bahn der Fläche L_D liegt, die aus einem L-förmigen Polygon mit geeigneten von D abhängigen Seitenlängen entsteht.
Während auch heute noch keine Translationsfläche mit Veech-Gruppe zweiter Art bekannt ist, fanden McMullen und unabhängig davon Hubert und Schmidt Konstruktionen unendlich erzeugter Veech-Gruppen erster Art. Eine Abschätzung des kritischen Exponenten dieser Gruppen war 10 Jahre lang eine wichtige offene Frage, die nun durch Theorem 1 beantwortet wird.
Zentral in der Konstruktion von Hubert und Schmidt sind spezielle Punkte, nämlich Verbindungspunkte. Hubert und Schmidt konstruieren Translationsflächen, deren Veech-Gruppen kommensurabel zum Stabilisator SL(X;P) von P sind und damit den gleichen kritischen Exponenten haben. Für Verbindungspunkte mit unendlicher SL(X)- Bahn (diese Punkte heißen nicht-periodisch) ist SL(X;P) unendlich erzeugt und von erster Art.
Wir zeigen Theorem 1, indem wir zeigen, dass für jedes D kongruent 0 mod 4, (kein Quadrat), und jeden nicht-periodischen Verbindungspunkt P in L_D der kritische Exponent der Gruppe SL(L_D;P) echt zwischen 1/2 und 1 liegt.
Eine natürliche Frage in diesem Zusammenhang ist die Abhängigkeit von P: Punkte Q in der SL(L_D)-Bahn von P sind auch er nicht-periodische Verbindungspunkte und die zugehö̈rigen Gruppen SL(L_D;P) und SL(L_D;Q) sind konjugiert zueinander. Daher widmen wir uns in Kapitel 4 der Bestimmung der Bahnen nicht-periodischer Verbindungspunkte.
Die Verbindungspunkte haben die Form P=(x_r+x_iw;y_r+y_iw) mit x_r,x_i,y_r,y_i aus Q. Wir zeigen, dass der Hauptnenner N(P) dieser (gekürzten) Brüche eine Invariante der Bahn ist. Daraus folgt:
Theorem 2. Es gibt unendlich viele verschiedene Bahnen von Verbindungspunkten von L_D.
Wir kennen die Operation der horizontalen und der vertikalen Scherungen A und B aus SL(L_D). Im Spezialfall D=8 erzeugen diese beiden Elemente die ganze Gruppe und wir geben je ein Verfahren an, um eine untere und eine obere Schranke an die Anzahl der Bahnen von nicht-periodischen Verbindungspunkten P mit fixiertem Hauptnenner N(P) zu finden. Damit zeigen wir:
Theorem 3. Die Menge der Verbindungspunkte P mit festem Wert N(P) zerfällt in eine endliche Anzahl von SL(L_8)-Bahnen.
Im Beweis von Theorem 1 ist es nötig, die Nicht-Mittelbarkeit eines Graphen zu zeigen. Da wir nur sehr wenige Informationen über dessen Struktur in unserer konkreten Situation haben, entwickeln wir in Kapitel 1 die folgende Methode:
Theorem 4. Sei G ein Graph, den man durch Weglassen von Kanten in einen Wald G′ ohne Blätter überführen kann, bei dem das Supremum der Längen von zusammenhängenden Valenz-2-Teilgraphen von G′ beschränkt ist. Dann ist G nicht mittelbar.
Um diese Methode anzuwenden, ordnen wir jeder Ecke P von G ein Komplexitätsmaß s(P) zu und weisen nach, dass dieser Wert für die Operation von Worten in A- und B-Potenzen mit wachsender Wortlänge ”tendenziell wächst“.
Die vorliegende Dissertation behandelt die Entwicklung eines Verkehrssimulationssystems, welches vollautomatisch aus Landkarten Simulationsgraphen erstellen kann. Der Fokus liegt bei urbanen Simulationsstudien in beliebigen Gemeinden und Städten. Das zweite fundamentale Standbein dieser Arbeit ist daher die Konstruktion von Verkehrsmodellen, die die wichtigsten Verkehrsteilnehmertypen im urbanen Bereich abbilden. Es wurden Modelle für Autos, Fahrräder und Fußgänger entwickelt.
Die Betrachtung des Stands der Forschung in diesem Bereich hat ergeben, dass die Verknüpfung von automatischer Grapherstellung und Modellen, die die Wechselwirkungen der verschiedenen Verkehrsteilnehmertypen abbilden, von keinem vorhandenen System geleistet wird. Es gibt grundlegend zwei Gruppen von Verkehrssimulationssystemen. Zum Einen existieren Systeme, die hohe Genauigkeiten an Simulationsergebnissen erzielen und dafür exakte (teil-)manuelle Modellierung der Gegebenheiten im zu simulierenden Bereich benötigen. Es werden in diesem Bereich meist Verkehrsmodelle simuliert, die die Verhaltensweisen der Verkehrsteilnehmer sehr gut abbilden und hierfür einen hohen Berechnungsaufwand benötigen. Auf der anderen Seiten existieren Simulationssysteme, die Straßengraphen automatisch erstellen können, darauf jedoch sehr vereinfachte Verkehrsmodelle simulieren. Es werden meist nur Autobewegungen simuliert. Der Nutzen dieser Herangehensweise ist die Möglichkeit, sehr große Szenarien simulieren zu können.
Im Rahmen dieser Arbeit wird ein System mit Eigenschaften beider grundlegenden Ansätze entwickelt, um multimodalen innerstädtischen Verkehr auf Basis automatisch erstellter Straßengraphen simulieren zu können. Die Entwicklung eines neuen Verkehrssimulationssystems erschien notwendig, da sich zum Zeitpunkt der Literaturbetrachtung kein anderes vorhandenes System für die Nutzung zur Erfüllung der genannten Zielstellung eignete. Das im Rahmen dieser Arbeit entwickelte System heißt MAINSIM (MultimodAle INnerstädtische VerkehrsSIMulation).
Die Simulationsgraphen werden aus Kartenmaterial von OpenStreetMap extrahiert. Kartenmaterial wird zuerst in verschiedene logische Layer separiert und anschließend zur Bestimmung eines Graphen des Straßennetzes genutzt. Eine Gruppe von Analyseschritten behebt Ungenauigkeiten im Kartenmaterial und ergänzt Informationen, die während der Simulation benötigt werden (z.B. die Verbindungsrichtung zwischen zwei Straßen). Das System verwendet Geoinformationssystemkomponenten zur Verarbeitung der Geodaten. Dies birgt den Vorteil der einfachen Erweiterbarkeit um weitere Datenquellen.
Die Verkehrssimulation verwendet mikroskopische Verhaltensmodelle. Jeder einzelne Verkehrsteilnehmer wird somit simuliert. Das Modell für Autos basiert auf dem in der Verkehrsforschung weit genutzten Nagel-Schreckenberg-Modell. Es verfügt jedoch über zahlreiche Modifikationen und Erweiterungen, um das Modell auch abseits von Autobahnen nutzen zu können und weitere Verhaltensweisen zu modellieren. Das Fahrradmodell entsteht durch geeignete Parametrisierung aus dem Automodell. Zur Entwicklung des Fußgängermodells wurde Literatur über das Verhalten von Fußgängern diskutiert, um daraus geeignete Eigenschaften (z.B. Geschwindigkeiten und Straßenüberquerungsverhaltensmuster) abzuleiten. MAINSIM ermöglicht folglich die Betrachtung des Verkehrsgeschehens auch aus der Sicht der Gruppe der Fußgänger oder Fahrradfahrer und kann deren Auswirkungen auf den Straßenverkehr einer ganzen Stadt bestimmen.
Das Automodell wurde auf Autobahnszenarien und innerstädtischen Straßengraphen evaluiert. Es konnte die gut verstandenen Zusammenhänge zwischen Verkehrsdichte, -fluss und -geschwindigkeit reproduzieren. Zur Evaluierung von Fahrradmodellen liegen nach dem besten Wissen des Autors keine Studien vor. Daher wurden an dieser Stelle der Einfluss der Fahrradfahrer auf den Straßenverkehr und die von Fahrrädern gefahrenen Geschwindigkeiten untersucht. Das Fußgängermodell konnte die aus der Literaturbetrachtung ermittelten Verhaltensweisen abbilden.
Nachdem die wichtigsten Komponenten von MAINSIM untersucht wurden, begannen Fallstudien, die verschiedene Gebiete abdecken. Die wichtigsten Ergebnisse aus diesem Teil der Arbeit sind:
- Es ist möglich, mit Hilfe maschineller Lernverfahren Staus innerhalb Frankfurts vorherzusagen.
- Nonkonformismus bezüglich der Verkehrsregeln kann je nach Verhalten den Verkehrsfluss empfindlich beeinflussen, kann aber auch ohne Effekt bleiben.
- Mit Hilfe von Kommunikationstechniken könnte in der Zukunft die Routenplanung von Autos verbessert werden. Ein Verfahren auf Basis von Pheromonspuren wurde im Rahmen dieser Arbeit untersucht.
- MAINSIM eignet sich zur Simulation großer Szenarien. In der letzten Fallstudie dieser Arbeit wurde der Autoverkehr eines Simulationsgebietes um Frankfurt am Main herum mit ca. 1,6 Mio. Trips pro Tag simuliert. Da MAINSIM über ein Kraftstoffverbrauchs- und CO2-Emissionsmodell verfügt, konnten die CO2-Emissionen innerhalb von Frankfurt ermittelt werden. Eine angekoppelte Simulation des Wetters mit Hilfe einer atmosphärischen Simulation zeigte, wie sich die Gase innerhalb Frankfurts verteilen.
Für den professionellen Einsatz in der Verkehrsforschung muss das entwickelte Simulationssystem um eine Methode zur Kalibrierung auf Sensordaten im Simulationsgebiet erweitert werden. Die vorhandenen Ampelschaltungen bilden nicht reale Ampeln ab. Eine Erweiterung des Systems um die automatische Integrierung maschinell lesbarer Schaltpläne von Ampeln im Bereich des Simulationsgebietes würde die Ergebnisgüte weiter erhöhen.
MAINSIM hat mehrere Anwendungsgebiete. Es können sehr schnell Simulationsgebiete modelliert werden. Daher bietet sich die Nutzung für Vorabstudien an. Wenn große Szenarien simuliert werden müssen, um z.B. die Verteilung der CO2-Emissionen innerhalb einer Stadt zu ermitteln, kann MAINSIM genutzt werden. Es hat sich im Rahmen dieser Arbeit gezeigt, dass Fahrräder und Fußgänger einen Effekt auf die Mengen des Kraftstoffverbrauchs von Autos haben können. Es sollte bei derartigen Szenarien folglich ein Simulationssysytem genutzt werden, welches die relevanten Verkehrsteilnehmertypen abbilden kann. Zur Untersuchung weiterer wissenschaftlicher Fragestellungen kann MAINSIM beliebig erweitert werden.
Zeitreihen von spontan auftretenden Topograpfien elektrischer Felder an der Kopfoberfläche, die durch eine Elektroenzephalografie (EEG) gemessen werden, zeigen Zeiträume („EEG-Microstates“), während denen die Topografie quasi-stabil ist. Diese EEG-Microstates werden üblicherweise dadurch analysiert, dass die zu spezifischen Zeitpunkten beobachteten Ausprägungen des EEGs in eine kleine Anzahl von prototypischen Topografien („Karten“) eingeteilt werden. Dadurch erhält man eine diskrete Kartensequenz.
Um die Struktur der Übergangswahrscheinlichkeiten in experimentellen Kartensequenzen zu beschreiben, werden diese Sequenzen durch eine reduzierte Markov-Kette modelliert mit nur einem Parameter pro Karte. Die Markov-Ketten können mithilfe von zwei bestimmten stochastischen Prozessen konstruiert werden. Durch den einen Prozess werden zufällige Intervalle definiert, die zufällig den verschiedenen Karten zugeordnet werden. Durch den anderen Prozess werden zufällige Abtastungszeitpunkte bestimmt, zu denen die Karte des jeweils aktuellen Intervalls abgelesen wird.
Neben der Motivation und Vorstellung des Markov-Ketten-Modells werden in dieser Arbeit Schätzer für die Modellparameter vorgeschlagen und diskutiert sowie ihre asymptotischen Varianzen hergeleitet. Zudem wird ein Anpassungstest durchgeführt und es werden Abwandlungen des Modells untersucht.
Ultrarelativistic Quantum Molecular Dynamics is a physics model to describe the transport, collision, scattering, and decay of nuclear particles. The UrQMD framework has been in use for nearly 20 years since its first development. In this period computing aspects, the design of code, and the efficiency of computation have been minor points of interest. Nowadays an additional issue arises due to the fact that the run time of the framework does not diminish any more with new hardware generations.
The current development in computing hardware is mainly focused on parallelism. Especially in scientific applications a high order of parallelisation can be achieved due to the superposition principle. In this thesis it is shown how modern design criteria and algorithm redesign are applied to physics frameworks. The redesign with a special emphasise on many-core architectures allows for significant improvements of the execution speed.
The most time consuming part of UrQMD is a newly introduced relativistic hydrodynamic phase. The algorithm used to simulate the hydrodynamic evolution is the SHASTA. As the sequential form of SHASTA is successfully applied in various simulation frameworks for heavy ion collisions its possible parallelisation is analysed. Two different implementations of SHASTA are presented.
The first one is an improved sequential implementation. By applying a more concise design and evading unnecessary memory copies, the execution time could be reduced to the half of the FORTRAN version’s execution time. The usage of memory could be reduced by 80% compared to the memory needed in the original version.
The second implementation concentrates fully on the usage of many-core architectures and deviates significantly from the classical implementation. Contrary to the sequential implementation, it follows the recalculate instead of memory look-up paradigm. By this means the execution speed could be accelerated up to a factor of 460 on GPUs.
Additionally a stability analysis of the UrQMD model is presented. Applying metapro- gramming UrQMD is compiled and executed in a massively parallel setup. The resulting simulation data of all parallel UrQMD instances were hereafter gathered and analysed. Hence UrQMD could be proven of high stability to the uncertainty of experimental data.
As a further application of modern programming paradigms a prototypical implementa- tion of the worldline formalism is presented. This formalism allows for a direct calculation of Feynman integrals and constitutes therefore an interesting enhancement for the UrQMD model. Its massively parallel implementation on GPUs is examined.
Spin(9)-invariant valuations
(2013)
The first aim of this thesis is to give a Hadwiger-type theorem for the exceptional Lie group Spin(9). The space of Spin(9)-invariant k-homogeneous valuations is studied through the construction of an exact sequence involving some spaces of differential forms. We present then a description of the spin representation using the properties of the 8-dimensional division algebra of the octonions. Using this description as well as representation-theoretic formulas, we can compute the dimensions of the spaces of differential forms appearing in the exact sequence. Hence we obtain the dimensions of the spaces of k-homogeneous Spin(9)-invariant valuations for k=0,1,...,16.
In the second part of this work, we construct one new element for a basis of one of these spaces. It is clear, that the k-th intrinsic volume is also Spin(9)-invariant. The last chapter of this work presents the construction of a new 2-homogeneous Spin(9)-invariant valuation. On a Riemannian manifold (M,g), we construct a valuation by integrating the curvature tensor over the disc bundle. We associate to this valuation on M a family of valuations on the tangent spaces. We show that these valuations are even and homogeneous of degree 2. Moreover, since the valuation on M is invariant under the action of the isometry group of M, the induced valuation on the tangent space in a point p in M is invariant under the action of the stabilisator of p for all p in M. In the special case where M is the octonionic projective plane, this construction yields an even, homogeneous of degree 2, Spin(9)-invariant valuation, whose Klain function is not constant, i.e. which is linearly independent of the second intrinsic volume.
This thesis presents various algorithms which have been developed for on-line event reconstruction in the CBM experiment at GSI, Darmstadt and the ALICE experiment at CERN, Geneve. Despite the fact that the experiments are different — CBM is a fixed target experiment with forward geometry, while ALICE has a typical collider geometry — they share common aspects when reconstruction is concerned.
The thesis describes:
— general modifications to the Kalman filter method, which allows one to accelerate, to improve, and to simplify existing fit algorithms;
— developed algorithms for track fit in CBM and ALICE experiment, including a new method for track extrapolation in non-homogeneous magnetic field.
— developed algorithms for primary and secondary vertex fit in the both experiments. In particular, a new method of reconstruction of decayed particles is presented.
— developed parallel algorithm for the on-line tracking in the CBM experiment.
— developed parallel algorithm for the on-line tracking in High Level Trigger of the ALICE experiment.
— the realisation of the track finders on modern hardware, such as SIMD CPU registers and GPU accelerators.
All the presented methods have been developed by or with the direct participation of the author.
In der modernen Hochschullehre haben sich eLearning-Elemente als ein Teil des Lehrrepertoires etabliert. Der Einsatz interaktiver webbasierter Selbstlernmodule (Web Based Trainings (WBT)) ist dabei eine Option. Hochschulen und Unternehmen versprechen sich dadurch neue Möglichkeiten des Lehrens und Lernens, um z. B. einen Ausgleich heterogener Vorerfahrungen sowie eine stärkere aktive Beteiligung der Lernenden zu bewirken. Damit die Erstellung und Strukturierung dieser Inhalte mit möglichst geringem Aufwand erfolgen kann, bieten Autorensysteme Unterstützung.
Zu den Grundfunktionen von Autorensystemen gehören unter anderem, das Einbinden gebräuchlicher Medienformate, die einfache Erstellung von Fragen sowie verschiedene Auswertungs- und Feedbackmöglichkeiten. Obwohl Autorensysteme schon vor vielen Jahren ihre erste praktische Anwendung fanden, gibt es nach wie vor Schwachstellen, die sich auf den gesamten Erstellungsprozess wie auch auf einzelne Funktionen beziehen. Im Detail wird bemängelt, dass die Werkzeuge zu komplex und unflexibel sind. Darüber hinaus fehlt häufig eine zufriedenstellende Verknüpfung der vielen Werkzeuge entlang der Prozesskette zu einer Gesamtlösung.
Des Weiteren wird die Konzentration auf die Produktionsphase kritisiert, wodurch andere wichtige Prozesse in den Hintergrund treten bzw. außer Acht gelassen werden.
Im Rahmen der Zusammenarbeit mit einem Automobilhersteller, für den die erste Version des Autorensystems LernBar weiterentwickelt wurde, spielte der Begriff „Lean Production“ inhaltlich in der Umsetzung der WBTs eine wesentliche Rolle. Die Lean Production, die über viele Jahre für die Automobilindustrie entwickelt, verbessert und angepasst wurde, liefert Optimierungsansätze für den Produktionsbereich. Ein wirtschaftlicher Nutzen des Lean-Ansatzes wird auch in anderen Bereichen gesehen wie z. B. in der Softwareentwicklung („Lean Software Development“) oder im Management („Lean Management“). Dabei bietet die Wertschöpfungsorientierung Lösungen für die widersprüchlichen Ziele mehr Leistungen zu geringeren Kosten, schneller und in höherer Qualität zugleich zu liefern. Aus der Grundidee der Lean Production entwickelte sich vorliegendes Dissertationsthema in Bezug darauf, inwiefern sich diese Prinzipien auf den WBT-Produktionsprozess übertragen lassen und die LernBar (das hierfür weiterentwickelnde Autorensystem) dabei Unterstützung bieten kann.
Zunächst wurde analysiert, welche Werkzeuge und Hilfestellungen benötigt werden, um unter dem Aspekt der Lean Production WBTs im universitären Umfeld erstellen zu können. In diesem Zusammenhang wurden Merkmale einer „Lean Media Production“ definiert sowie konzeptionell und technisch umgesetzt. Zur Verbesserung der Prozesse flossen Ergebnisse aus empirischer und praktischer Forschung ein. Im Vergleich zu anderen Entwicklungen bei denen häufig das Hauptziel eine umfangreiche Funktionalität ist, werden u.a. folgende übertragbare Ziele bei der Umsetzung verfolgt: Verschwendung vermeiden, eine starke Einbeziehung der Kunden, Werkzeuge die nahtlos ineinandergreifen, eine hohe Flexibilität und eine stetige Qualitätsverbesserung.
Zur Erreichung dieser Zielsetzungen wurden alle Prozesse kontinuierlich verbessert, sich auf das Wesentliche und die Wertschöpfung konzentriert sowie überflüssige Schritte eliminiert. Demnach ist unter dem Begriff „Lean Media Production“ ein skalierbarer, effizienter und effektiver Produktionsprozess zu verstehen, in dem alle Werkzeuge ineinandergreifen.
Die Realisierung der „Lean Media Production“ erfolgte anhand des Autorensystems LernBar, wobei die typischen Softwareentwicklungsphasen Entwurf, Implementierung und Evaluierung mehrfach durchlaufen wurden. Ausschlaggebend dabei war, dass der „Lean“-Aspekt berücksichtigt wurde und dies somit eine neue Vorgehensweise bei der Umsetzung eines Autorensystems darstellt. Im Verlauf der Entwicklungen ergaben sich, durch eine formative Evaluation, den Einsatz in Projekten und eine empirische Begleitforschung, neue Anforderungen an das System. Ein Vergleich der zwei Produktionssysteme, Automobil vs. WBT-Produktion, zeigt und bestätigt die Erwartung, dass nicht alle Prinzipien der Lean Production übertragbar sind.
Dennoch war diese Untersuchung notwendig, da sie Denkanstöße zur Entwicklung und Optimierung des Erstellungsprozesses eines WBTs gab. Auch die Ergebnisse der abschließenden Online-Befragung ergaben, dass die Ziele der Arbeit erreicht wurden, dass aber weiterer Optimierungsbedarf besteht. Die LernBar Release 3 bietet für alle Produktionsphasen Werkzeuge an, durch die eine effektive und effiziente Erstellung von WBTs von der Idee bis zur Distribution möglich ist.
Stand noch vor fünf Jahren zu Beginn dieser Arbeit das Endprodukt bei der LernBar Entwicklung im Vordergrund, verlagerte sich durch den Einfluss dieser Dissertation der Schwerpunkt auf den gesamten Produktionsprozess. Unter Berücksichtigung der in diesem Zusammenhang entwickelten Prinzipien einer „Lean Media Production“, nehmen bspw. die Wirtschaftlichkeit und die starke Kundenorientierung während des Produktionsprozesses einen wichtigen Stellenwert ein. Dieser Ansatz ist eine neue Vorgehensweise im Bereich der Entwicklung von Autorensystemen, der seine Anerkennung und Professionalität durch die Ergebnisse des selbstentwickelten Evaluationsbogens sowie dem stetig wachsenden Einsatz in Schulen, Hochschulen und Unternehmen belegen kann.
In weiteren Forschungsarbeiten ist zu untersuchen, welche Lean Production Prinzipien zu verwenden oder anzupassen sind, wenn z. B. in größeren Teams oder mobil produziert wird. Des Weiteren sollte überprüft werden, inwieweit die Lernenden mit dem Endprodukt zufrieden sind und in ihrem Lernprozess unterstützt werden. Durch diese Forschungsarbeit wurde ein Beitrag dazu geleistet, die Lehre und Ausbildung zu optimieren, indem die Autoren/Lehrende in der Erstellung ihrer digitalen Lerninhalte im gesamten Prozess von aufeinander abgestimmten Werkzeugen unterstützt werden.
The Project European Privacy Open Space (PrivacyOS) aims at bringing together industry, SMEs, Government, Academia and Civil Society to foster development and deployment of privacy infrastructures for Europe. The general objectives of PrivacyOS are to create a longterm collaboration in the thematic network and establish collective interfaces with other EU projects. Participants exchange research and best practices, as well as develop strategies and joint projects following four core policy goals: Awareness-rising, enabling privacy on the Web, fostering privacy-friendly Identity Management, and stipulating research.
...
This report focuses on the 3rd PrivacyOS conference, which was held in Vienna, October 26th and 27th 2009, co-located with the Austrian Big Brother Awards. 50 participants attended the conference and devised the agenda with 21 presentations in two parallel tracks. The topics of the presentations discussed included, amongst others: data protection awareness, data protection in healthcare, data protection in the Web 2.0, privacy-related technologies such as EnCoRe, TOR or Microformats as well as regulatory, cultural and sociological implications of data protection. Also at the 3rd PrivacyOS conference the software product “KiwiSecurity” was awarded the EuroPriSe Seal (European Privacy Seal, www.european-privacy-seal.eu). EuroPriSe is an initiative of the data protection authority Unabhängiges Landeszentrum für Datenschutz Schleswig-Holstein (ULD), Germany. It has been started as a European Project under the eTEN programme.