Three-way optimisation of response time, subtask dispersion and energy consumption in split-merge systems

This paper investigates various ways in which the triple trade-off metrics between task response time, subtask dispersion and energy can be improved in split-merge queueing systems. Four ideas, namely dynamic subtask dispersion reduction, state-dependent service times, multiple redundant subtask service servers and restarting subtask service, are examined in the paper. It transpires that all four techniques can be used to improve the triple trade-off, while combinations of the techniques are not necessarily beneficial

Обзор систем параллельной обработки заявок

This paper is the first in a series of two articles devoted to the review of “fork-join” (inthe western classification) queuing systems or systems with the splitting of incoming queries.This system is a natural model for many other real systems. The article describes the fork-joinqueueing model construction and main characteristics of this model. Special attention is paid tomethods of analysis of the response time of the system. Since the exact expression for the meanresponse time is known only for the case of two servers, the article gives a detailed descriptionof the approach to obtaining an accurate expression of this characteristic. For the case whenthe number of servers is more than two, approximations of the mean response time are obtainedby different methods, which is explained by the complexity of the studies due to the existingdependence between the queues of subqueries due to common arrival moments. The paperpresents several methods of approximate analysis: various variants of empirical approximation,i.e. methods that refine the obtained characteristics by using the results of simulation modeling;interpolation methods using system load limit values in cases when the incoming flow and servicetime distributions are not exponential.Данная работа является первой в серии из двух статей, посвящённых обзору систем массового обслуживания вида «fork-join» (в западной классификации) или системам с расщеплением запросов. Указанная система является естественной моделью для многих других реальных систем. В статье описаны особенности построения этой модели и родственных ей систем, основные их характеристики. Отдельное внимание уделяется методам анализа времени отклика системы. Поскольку точное выражение для среднего времени отклика известно только для случая двух приборов, в статье приведено подробное описание подхода к получению точного выражения этой характеристики. Для случая, когда число приборов больше двух, различными методами получены аппроксимации среднего времени отклика,что объясняется сложностью исследований из-за существующей зависимости между очередями под запросов в силу общих моментов поступления. В работе представлено несколько методов приближенного анализа: различные варианты эмпирической аппроксимации, т.е. методы, уточняющие полученные характеристики благодаря использованию результатов имитационного моделирования; интерполяция с помощью предельных значений загрузки системы в случаях с отличными от экспоненциального распределениями для входящего потока и времени обслуживания

Обзор систем параллельной обработки заявок. Часть II

This paper is a continuation of the survey of the “fork-join” queuing systems (in the westernclassification) or the systems with splitting of queries. Interest in such systems is explainedby a wide range of problems that can be solved with their help, since in fact it is a matter ofparallel processing of data and their applications. For example, this may concern the analysis ofdisk arrays, cloud computing, high-performance services and even the process of picking ordersin a warehouse. In the first part of the survey, the main features of the described model (andrelated systems) and its construction were introduced. Also the detailed description of theapproach to obtaining an accurate expression of the average response time in the case of twodevices was presented as well as several methods of approximate analysis of this characteristic(the case when the number of devices is more than two). This part of the survey is devotedto the description of other existing methods for approximating the average response time. Inparticular, the approaches of the approximate analysis of the response time are as follows: thematrix-geometric method, the analysis with the help of order statistics for various types ofdistribution of the service time of subqueries.Данная работа является продолжением обзора методов исследования системы массовогообслуживания вида «fork-join» (в западной классификации) или системы с расщеплениемзапросов. Интерес к рассматриваемой системе объясняется широким спектром задач, которые могут быть решены с её помощью, поскольку фактически речь идёт о параллельнойобработке данных и их приложениях. К примеру, это может касаться анализа работы дисковых массивов, облачных вычислений, высокопроизводительных сервисов и даже процессакомплектации заказов на складе. Если в первой части обзора были описаны особенностипостроения данной модели и родственных ей систем, а также приведено подробное описание подхода к получению точного выражения среднего времени отклика в случае двухприборов и представлено несколько методов приближенного анализа данной характеристики в случае, когда число приборов больше двух, то во второй части обзора представленоописание других существующих методов аппроксимации среднего времени отклика. В частности, к рассматриваемым подходам приближенного анализа времени отклика относятся:матрично-геометрический метод, анализ с помощью порядковых статистик для различныхтипов распределения времени пребывания подзапросов

Corridor Location: Generating Competitive and Efficient Route Alternatives

The problem of transmission line corridor location can be considered, at best, a "wicked" public systems decision problem. It requires the consideration of numerous objectives while balancing the priorities of a variety of stakeholders, and designers should be prepared to develop diverse non-inferior route alternatives that must be defensible under the scrutiny of a public forum. Political elements aside, the underlying geographical computational problems that must be solved to provide a set of high quality alternatives are no less easy, as they require solving difficult spatial optimization problems on massive GIS terrain-based raster data sets.Transmission line siting methodologies have previously been developed to guide designers in this endeavor, but close scrutiny of these methodologies show that there are many shortcomings with their approaches. The main goal of this dissertation is to take a fresh look at the process of corridor location, and develop a set of algorithms that compute path alternatives using a foundation of solid geographical theory in order to offer designers better tools for developing quality alternatives that consider the entire spectrum of viable solutions. And just as importantly, as data sets become increasingly massive and present challenging computational elements, it is important that algorithms be efficient and able to take advantage of parallel computing resources.A common approach to simplify a problem with numerous objectives is to combine the cost layers into a composite a priori weighted single-objective raster grid. This dissertation examines new methods used for determining a spatially diverse set of near-optimal alternatives, and develops parallel computing techniques for brute-force near-optimal path enumeration, as well as more elegant methods that take advantage of the hierarchical structure of the underlying path-tree computation to select sets of spatially diverse near optimal paths.Another approach for corridor location is to simultaneously consider all objectives to determine the set of Pareto-optimal solutions between the objectives. This amounts to solving a discrete multi-objective shortest path problem, which is considered to be NP-Hard for computing the full set of non-inferior solutions. Given the difficulty of solving for the complete Pareto-optimal set, this dissertation develops an approximation heuristic to compute path sets that are nearly exact-optimal in a fraction of the time when compared to exact algorithms. This method is then applied as an upper bound to an exact enumerative approach, resulting in significant performance speedups. But as analytic computing continues to moved toward distributed clusters, it is important to optimize algorithms to take full advantage parallel computing. To that extent, this dissertation develops a scalable parallel framework that efficiently solves for the supported/convex solutions of a biobjective shortest path problem. This framework is equally applicable to other biobjective network optimization problems, providing a powerful tool for solving the next generation of location analysis and geographical optimization models

Combining automated processing and customized analysis for large-scale sequencing data

Extensive application of high-throughput methods in life sciences has brought substantial new challenges for data analysis. Often many different steps have to be applied to a large number of samples. Here, workflow management systems support scientists through the automated execution of corresponding large analysis workflows. The first part of this cumulative dissertation concentrates on the development of Watchdog, a novel workflow management system for the automated analysis of large-scale experimental data. Watchdog`s main features include straightforward processing of replicate data, support for distributed computer systems, customizable error detection and manual intervention into workflow execution. A graphical user interface enables workflow construction using a pre-defined toolset without programming experience and a community sharing platform allows scientists to share toolsets and workflows efficiently. Furthermore, we implemented methods for resuming execution of interrupted or partially modified workflows and for automated deployment of software using package managers and container virtualization. Using Watchdog, we implemented default analysis workflows for typical types of large-scale biological experiments, such as RNA-seq and ChIP-seq. Although they can be easily applied to new datasets of the same type, at some point such standard workflows reach their limit and customized methods are required to resolve specific questions. Hence, the second part of this dissertation focuses on combining standard analysis workflows with the development of application-specific novel bioinformatics approaches to address questions of interest to our biological collaboration partners. The first study concentrates on identifying the binding motif of the ZNF768 transcription factor, which consists of two anchor regions connected by a variable linker region. As standard motif finding methods detected only the anchors of the motifs separately, a custom method was developed for determining the spaced motif with the linker region. The second study focused on the effect of CDK12 inhibition on transcription. Results obtained from standard RNA-seq analysis indicated substantial transcript shortening upon CDK12 inhibition. We thus developed a new measure to quantify the degree of transcript shortening. In addition, a customized meta-gene analysis framework was developed to model RNA polymerase II progression using ChIP-seq data. This revealed that CDK12 inhibition causes an RNA polymerase II processivity defect resulting in the detected transcript shortening. In summary, the methods developed in this thesis represent both general contributions to large-scale sequencing data analysis and served to resolve specific questions regarding transcription factor binding and regulation of elongating RNA Polymerase II

Performance measurement and analysis of PC based cluster server using SET of Architecture and modeling a scalable High performance cluster

Not availabl

Mapping the Genomic Context of Mutagenesis

The accumulation of genomic mutations leads to the formation of cancer. For this reason, many efforts have been undertaken to characterise mutational processes in terms of their genomic imprints. A particularly successful approach is matrix-based mutational signature analysis, which identifies prototypical mutation patterns by applying non-negative matrix factorisation to catalogues of single nucleotide variants and other mutation types. However, mutagenesis is a multifaceted event that is affected by the genomic organisation of DNA and cellular processes such as transcription, replication, and DNA repair processes. Moreover, since many mutational processes also generate characteristic multi nucleotide variants, insertion and deletions, and structural variants, it appears valuable to jointly deconvolve broader mutational catalogues to better understand the complex nature of mutagenesis. In this thesis, I present TensorSignatures, an algorithm to learn mutational signatures jointly across different variant categories as well as their genomic localisation and properties. The analysis of 2,778 primary and 3,824 metastatic cancer genomes of the PCAWG consortium and the HMF cohort shows that practically all signatures operate dynamically in response to various genomic and epigenomic states. The analysis pins differential spectra of UV mutagenesis found in active and inactive chromatin to global genome nucleotide excision repair. TensorSignatures accurately characterises transcription-associated mutagenesis, which is detected in 7 different cancer types. The algorithm also extracts distinct signatures of replication- and double strand break repair-driven mutagenesis by APOBEC3A and 3B with differential numbers and length of mutation clusters. As a fourth example, TensorSignatures reproduces a signature of somatic hypermutation generating highly clustered variants around the transcription start sites of active genes in lymphoid leukaemia, distinct from a more general and less clustered signature of Polη-driven translesion synthesis found in a broad range of cancer types. Finally, I demonstrate TensorSignatures’ utility by applying it to multiple datasets in various collaboration projects. Taken together, TensorSignatures adds great detail and refines mutational signature analysis by jointly learning mutation patterns and their genomic determinants. This sheds light on the manifold influences that underlie mutagenesis and helps to pinpoint mutagenic influences which cannot easily be distinguished based on the mutation spectra alone. As mutational signature analysis is an essential element of the cancer genome analysis toolkit, TensorSignatures may help make the growing catalogues of mutational signatures more insightful by highlighting mutagenic mechanisms, or hypotheses thereof, to be investigated in greater depth

Nuclear Fusion Programme: Annual Report of the Association Karlsruhe Institute of Technology/EURATOM ; January 2013 - December 2013 (KIT Scientific Reports ; 7671)

The Karlsruhe Institute of Technology (KIT) is working in the framework of the European Fusion Programme on key technologies in the areas of superconducting magnets, microwave heating systems (Electron-Cyclotron-Resonance-Heating, ECRH), the deuterium-tritium fuel cycle, He-cooled breeding blankets, a He-cooled divertor and structural materials, as well as refractory metals for high heat flux applications including a major participation in the preparation of the international IFMIF project