Emergent systems in high-performance computing (HPC) expect maximal efficiency to achieve the goal of power budget under 20-40 megawatts for 1 exaflop set by the Department of Energy. To optimize efficiency, emergent systems provide multiple power-performance control techniques to throttle different system components and scale of concurrency. In this dissertation, we focus on three throttling techniques: CPU dynamic voltage and frequency scaling (DVFS), dynamic memory throttling (DMT), and dynamic concurrency throttling (DCT). We first conduct an empirical analysis of the performance and energy trade-offs of different architectures under the throttling techniques. We show the impact on performance and energy consumption on Intel x86 systems with accelerators of Intel Xeon Phi and a Nvidia general-purpose graphics processing unit (GPGPU). We show the trade-offs and potentials for improving efficiency. Furthermore, we propose a parallel performance model for coordinating DVFS, DMT, and DCT simultaneously. We present a multivariate linear regression-based approach to approximate the impact of DVFS, DMT, and DCT on performance for performance prediction. Validation using 19 HPC applications/kernels on two architectures (i.e., Intel x86 and IBM BG/Q) shows up to 7% and 17% prediction error correspondingly. Thereafter, we develop the metrics for capturing the performance impact of DVFS, DMT, and DCT. We apply the artificial neural network model to approximate the nonlinear effects on performance impact and present a runtime control strategy accordingly for power capping. Our validation using 37 HPC applications/kernels shows up to a 20% performance improvement under a given power budget compared with the Intel RAPL-based method. / Ph. D. / System efficiency on high-performance computing (HPC) systems is the key to achieving the goal of power budget for exascale supercomputers. Techniques for adjusting the performance of different system components can help accomplish this goal by dynamically controlling system performance according to application behaviors. In this dissertation, we focus on three techniques: adjusting CPU performance, memory performance, and the number of threads for running parallel applications. First, we profile the performance and energy consumption of different HPC applications on both Intel systems with accelerators and IBM BG/Q systems. We explore the trade-offs of performance and energy under these techniques and provide optimization insights. Furthermore, we propose a parallel performance model that can accurately capture the impact of these techniques on performance in terms of job completion time. We present an approximation approach for performance prediction. The approximation has up to 7% and 17% prediction error on Intel x86 and IBM BG/Q systems respectively under 19 HPC applications. Thereafter, we apply the performance model in a runtime system design for improving performance under a given power budget. Our runtime strategy achieves up to 20% performance improvement to the baseline method.

Purpose – The presented research aims to explain, describe and analyze the process of dynamic strategy development in high growth firms. Accordingly the research seeks to investigate how dynamic strategies are used within high growth firms and how strategic learning affects the process. Design/methodology/approach – The authors presents a review of theoretically relevant studies of high growth related to strategy, and two original studies examining the impact of dynamic strategy on high growth. A theoretical framework for the study of dynamic strategy processes is developed. The study comprehends eight interviews divided over five high growth firms, where high growth is defined by the OECD (2008) standard. Findings – In the study, the researchers finds significant evidence for the active and deliberate use of dynamic strategy in the high growth firms of the study. The implication of strategic learning on the dynamic strategies is found to be substantial. The findings shows that dynamic strategy development are used to a large extent and considered vital for achieving growth within in the high growth firms of the study. Research/theoretical implications/limitations – The findings demonstrate that dynamic strategy development is actively used in high growth phases of the firms studied. This has implications on the extension of previous research, as it shows the actual use of dynamic strategy and further emphasizes the importance of strategic learning within this process. With the important limitation that the study is considered too small to generalize over a larger population, which implies that further research on the subject is needed. Managerial implications – The findings provide guidelines for managers of how to handle strategy development in high growth, however due to the previous limitation this is presented as the way the high growth firms within this study handles this development. The guidelines could be used by anyone in managerial positions, thus increasing the understanding of how high growth firms handle strategy.

The research work reported in the thesis deals with the development of dynamic covalent systems and their applications in evaluation and screening of protein-ligands and enzyme inhibitors, as well as in synthetic methodologies. The thesis is divided into four parts as described below. In part one, synthetic methodologies to access 3-functionalized phthalides and 3-thioisoindolinones using the concept of cascade reactions are demonstrated. Efficient syntheses of the target products are designed and performed in one-pot process under mild reaction conditions.  In part two, phosphine-catalyzed disulfide metathesis for the generation of dynamic carbohydrate system in aqueous solution is demonstrated. In the presence of biological target (Concanavalin A), the optimal dynamic ligand is successfully identified in situ by the 1H STD-NMR spectroscopy. In part three, lipase-catalyzed resolutions of dynamic reversible systems using reversible cyanohydrin and hemithioacetal reactions in one-pot processes are demonstrated. The dynamic systems are generated under thermodynamic control in organic solution and subsequently resolved by lipase-mediated resolution under kinetic control. The resolution processes resulted in the lipase-selected substrates with high structural and stereochemical specificities. In the last part, dynamic fragment-based strategy is presented using β-galactosidase as a model target enzyme. Based on our previous study, the best dynamic inhibitor of β-galactosidase was identified using 1H STD-NMR technique from dynamic hemithioacetal systems. The structure of the dynamic inhibitor is tailored by fragment linking and optimization processes. The designed inhibitor structures are then synthesized and tested for inhibition activities against β-galactosidase. / QC 20110526

This  thesis  is  divided  into  four  parts,  all  centered  around  Constitutional Dynamic  Chemistry  (CDC)  and  Dynamic  Kinetic  Resolution  (DKR)  using biocatalysts for selective transformations, and their applications in screening of bioactive compounds, organic synthesis, and enzyme classification.    In  part  one,  an  introduction  to  CDC  and  DKR  is  presented,  illustrating  the basic  concepts,  practical  considerations  and  potential  applications  of  such dynamic systems, thus providing the background information for the studies in the following chapters.   In part two, Dynamic Systemic Resolution (DSR), a concept based on CDC is exemplified.  With  enzyme-catalyzed  transformations  as  external  selection pressure,  optimal  structures  can  be  selected  and  amplified  from  the  system. This  concept  is  expanded  to  various  types  of  dynamic  systems  containing single, double cascade/parallel, and multiple reversible reactions. In addition, the  substrate  selectivity  and  catalytic  promiscuity  of  target  enzymes  are  also investigated.   In   part   three,   DKR   protocols   using   reversible   reactions   for   substrate racemizations  are  illustrated.  Biocatalysts  are  here  employed  for  asymmetric transformations,  resulting  in  efficient  synthetic  pathways  for  enantioenriched organic compounds.   Part  four  demonstrates  two  unique  applications  of  CDC:  one  resulting  in enzyme  classification  by  use  of  pattern  recognition  methodology;  the  other involving  enzyme  self-inhibition  through  in  situ  transformation  of  stealth inhibitors employing the catalytic activity of the target enzyme. / <p>QC 20130614</p>

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Submitted by Rafael Santana (rafael.silvasantana@ufpe.br) on 2017-05-11T18:10:34Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Versão Atualizada Tese Eric Ferreira de Oliveira.pdf: 1865683 bytes, checksum: 517608a245f6372afd45b3bba78733d6 (MD5) / Made available in DSpace on 2017-05-11T18:10:34Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Versão Atualizada Tese Eric Ferreira de Oliveira.pdf: 1865683 bytes, checksum: 517608a245f6372afd45b3bba78733d6 (MD5) Previous issue date: 2016-02-29 / CNEN / O estado da arte dos métodos aplicados para processos industriais é atualmente baseado em princípios de reconstruções tomográficas clássicas desenvolvidos para padrões tomográficos de distribuições estáticas, ou seja, são limitados a processos de pouca variabilidade. Ruídos e artefatos de movimento são os principais problemas causados pela incompatibilidade nos dados gerada pelo movimento. Além disso, em processos tomográficos industriais é comum um número limitado de dados podendo produzir ruído, artefatos e não concordância com a distribuição em estudo. Um dos objetivos do presente trabalho é discutir as dificuldades que surgem da implementação de algoritmos de reconstrução em tomografia dinâmica que foram originalmente desenvolvidos para distribuições estáticas. Outro objetivo é propor soluções que visam reduzir a perda de informação temporal devido a utilização de técnicas estáticas em processos dinâmicos. No que diz respeito à reconstrução de imagem dinâmica foi realizada uma comparação entre diferentes métodos de reconstrução estáticos, como MART e FBP, quando usado para cenários dinâmicos. Esta comparação foi baseada em simulações por MCNPX, e também analiticamente, de um cilindro de alumínio que se move durante o processo de aquisição, e também com base em imagens de cortes transversais de técnicas de CFD. Outra contribuição foi aproveitar o canal triplo de cores necessário para exibir imagens coloridas na maioria dos monitores, de modo que, dimensionando adequadamente os valores adquiridos de cada vista no sistema linear de reconstrução, foi possível imprimir traços temporais na imagem tradicionalmente reconstruída. Finalmente, uma técnica de correção de movimento usado no campo da medicina foi proposto para aplicações industriais, considerando-se que a distribuição de densidade nestes cenários pode apresentar variações compatíveis com movimentos rígidos ou alterações na escala de certos objetos. A ideia é usar dados conhecidos a priori ou durante o processo, como vetor deslocamento, e então usar essas informações para melhorar a qualidade da reconstrução. Isto é feito através da manipulação adequada da matriz peso no método algébrico, isto é, ajustando-se os valores para refletir o movimento objeto do previsto ou deformação. Os resultados de todas essas técnicas aplicadas em vários experimentos e simulações são discutidos neste trabalho. / The state of the art methods applied to industrial processes is currently based on the principles of classical tomographic reconstructions developed for tomographic patterns of static distributions, or is limited to cases of low variability of the density distribution function of the tomographed object. Noise and motion artifacts are the main problems caused by a mismatch in the data from views acquired in different instants. All of these add to the known fact that using a limited amount of data can result in the presence of noise, artifacts and some inconsistencies with the distribution under study. One of the objectives of the present work is to discuss the difficulties that arise from implementing reconstruction algorithms in dynamic tomography that were originally developed for static distributions. Another objective is to propose solutions that aim at reducing a temporal type of information loss caused by employing regular acquisition systems to dynamic processes. With respect to dynamic image reconstruction it was conducted a comparison between different static reconstruction methods, like MART and FBP, when used for dynamic scenarios. This comparison was based on a MCNPx simulation as well as an analytical setup of an aluminum cylinder that moves along the section of a riser during the process of acquisition, and also based on cross section images from CFD techniques. As for the adaptation of current tomographic acquisition systems for dynamic processes, this work established a sequence of tomographic views in a just-in-time fashion for visualization purposes, a form of visually disposing density information as soon as it becomes amenable to image reconstruction. A third contribution was to take advantage of the triple color channel necessary to display colored images in most displays, so that, by appropriately scaling the acquired values of each view in the linear system of the reconstruction, it was possible to imprint a temporal trace into the regularly reconstructed image, where the temporal trace utilizes a channel and the regular reconstruction utilizes a different one. Finally, a motion correction technique used in the medical field was proposed for industrial applications, considering that the density distribution in these scenarios may present variations compatible with rigid motions or changes in scale of certain objects. The idea is to identify in some configurations of the temporarily distributed data clues of the type of motion or deformation suffered by the object during the data acquisition, and then use this information to improve the quality of the reconstruction. This is done by appropriately manipulating the weight matrix in the algebraic method, i.e., by adjusting the values to reflect the predicted object motion or deformation. The results of all these techniques applied in several experiments and simulations are discussed in this work.

In recent years there has been an increasing interest in dynamic taint tracing of compiled software as a powerful analysis method for security and other purposes. Most existing approaches are highly application specific and tends to sacrifice precision in favor of performance. In this thesis project a generic taint tracing tool has been developed that can deliver high precision taint information. By allowing an arbitrary number of taint labels to be stored for every tainted byte, accurate taint propagation can be achieved for values that are derived from multiple input bytes. The tool has been developed for x86 Linux systems using the dynamic binary instrumentation framework Valgrind. The basic theory of taint tracing and multi-label taint propagation is discussed, as well as the main concepts of implementing a taint tracing tool using dynamic binary instrumentation. The impact of multi-label taint propagation on performance and precision is evaluated. While multi-label taint propagation has a considerable impact on performance, experiments carried out using the tool show that large amounts of taint information is lost with approximate methods using only one label per tainted byte.

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