Дисертації з теми "Mixed precision"
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Omland, Steffen [Verfasser]. "Mixed Precision Multilevel Monte Carlo Algorithms for Reconfigurable Computing Systems / Steffen Omland." München : Verlag Dr. Hut, 2016. http://d-nb.info/1113336447/34.
McEntee, Peter John. "The integration and validation of precision management tools in mixed farming systems." Thesis, Curtin University, 2016. http://hdl.handle.net/20.500.11937/54060.
Steffy, Daniel E. "Topics in exact precision mathematical programming." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39639.
Gerest, Matthieu. "Using Block Low-Rank compression in mixed precision for sparse direct linear solvers." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS447.
In order to solve large sparse linear systems, one may want to use a direct method, numerically robust but rather costly, both in terms of memory consumption and computation time. The multifrontal method belong to this class algorithms, and one of its high-performance parallel implementation is the solver MUMPS. One of the functionalities of MUMPS is the use of Block Low-Rank (BLR) matrix compression, that improves its performance. In this thesis, we present several new techniques aiming at further improving the performance of dense and sparse direct solvers, on top of using a BLR compression. In particular, we propose a new variant of BLR compression in which several floating-point formats are used simultaneously (mixed precision). Our approach is based on an error analysis, and it first allows to reduce the estimated cost of a LU factorization of a dense matrix, without having a significant impact on the error. Second, we adapt these algorithms to the multifrontal method. A first implementation uses our mixed-precision BLR compression as a storage format only, thus allowing to reduce the memory footprint of MUMPS. A second implementation allows to combine these memory gains with time reductions in the triangular solution phase, by switching computations to low precision. However, we notice performance issues related to BLR for this phase, in case the system has many right-hand sides. Therefore, we propose new BLR variants of triangular solution that improve the data locality and reduce data movements, as highlighted by a communication volume analysis. We implement our algorithms within a simplified prototype and within solver MUMPS. In both cases, we obtain time gains
Wolfram, Heiko. "Model Building, Control Design and Practical Implementation of a High Precision, High Dynamical MEMS Acceleration Sensor." Universitätsbibliothek Chemnitz, 2005. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200501921.
Bustamante, Danilo. "High-Precision, Mixed-Signal Mismatch Measurement of Metal-Oxide-Metal Capacitors and a 13-GHz 5-bit 360-Degree Phase Shifter." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/9240.
Geifman, Nophar, Richard E. Kennedy, Lon S. Schneider, Iain Buchan, and Roberta Diaz Brinton. "Data-driven identification of endophenotypes of Alzheimer’s disease progression: implications for clinical trials and therapeutic interventions." BIOMED CENTRAL LTD, 2018. http://hdl.handle.net/10150/627086.
Di, Pace Brian S. "Site- and Location-Adjusted Approaches to Adaptive Allocation Clinical Trial Designs." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5706.
Zulian, Marine. "Méthodes de sélection et de validation de modèles à effets mixtes pour la médecine génomique." Thesis, Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAX003.
The study of complex biological phenomena such as human pathophysiology, pharmacokinetics of a drug or its pharmacodynamics can be enriched by modelling and simulation approaches. Technological advances in genetics allow the establishment of data sets from larger and more heterogeneous populations. The challenge is then to develop tools that integrate genomic and phenotypic data to explain inter-individual variability. In this thesis, we develop methods that take into account the complexity of biological data and the complexity of underlying processes. Curation steps of genomic covariates allow us to limit the number of potential covariates and limit correlations between covariates. We propose an algorithm for selecting covariates in a mixed effects model whose structure is constrained by the physiological process. In particular, we illustrate the developed methods on two medical applications: actual high blood pressure data and simulated tramadol (opioid) metabolism data
Cardoso, Adilson Silva. "Design and characterization of BiCMOS mixed-signal circuits and devices for extreme environment applications." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53099.
Rappaport, Ari. "Estimations d'erreurs a posteriori et adaptivité en approximation numérique des EDPs : régularisation, linéarisation, discrétisation et précision en virgule flottante." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS057.
This thesis concerns a posteriori error analysis and adaptive algorithms to approximately solve nonlinear partial differential equations (PDEs). We consider PDEs of both elliptic and degenerate parabolic type. We also study adaptivity in floating point precision of a multigrid solver of systems of linear algebraic equations. In the first two chapters, we consider elliptic PDEs arising from an energy minimization problem. The a posteriori analysis therein is based directly on the difference of the energy in the true and approximate solution. The nonlinear operators of the elliptic PDEs we consider are strongly monotone and Lipschitz continuous. In this context, an important quantity is the “strength of the nonlinearity” given by the ratio L/α where L is the Lipschitz continuity constant and α is the (strong) monotonicity constant. In Chapter 1 we study an adaptive algorithm comprising adaptive regularization, discretization, and linearization. The algorithm is applied to an elliptic PDE with a nonsmooth nonlinearity. We derive a guaranteed upper bound based on primal-dual gap based estimator. Moreover, we isolate components of the error corresponding to regularization, discretization, and linearization that lead to adaptive stopping criteria. We prove that the component estimators converge to zero in the respective limits of regularization, discretization, and linearization steps of the algorithm. We present numerical results demonstrating the effectiveness of the algorithm. We also present numerical evidence of robustness with respect to the aforementioned ratio L/α which motivates the work in the second chapter. In Chapter 2, we consider the question of efficiency and robustness of the primal-dual gap error estimator. We in particular consider an augmented energy difference, for which we establish independence of the ratio L/α (robustness) for the Zarantonello linearization and only patch-local and computable dependence for other linearization methods including the Newton linearization. Numerical results are presented to substantiate the theoretical developments. In Chapter 3 we turn our attention to the problem of adaptive regularization for the Richards equation. The Richards equation appears in the context of porous media modeling. It contains nonsmooth nonlinearities, which are amenable to the same approach we adopt in Chapter 1. We develop estimators and an adaptive algorithm where the estimators are inspired by estimators based on the dual norm of the residual. We test our algorithm on a series of numerical examples coming from the literature. In Chapter 4 we provide details for an efficient implementation of the equilibrated flux, a crucial ingredient in computing the error estimators so far discussed. The implementation relies on the multi-threading paradigm in the Julia programming language. An additional loop is introduced to avoid memory allocations, which is crucial to obtain parallel scaling. In Chapter 5 we consider a mixed precision iterative refinement algorithm with a geometric multigrid method as the inner solver. The multigrid solver inherently provides an error estimator of the algebraic error which we use in the stopping criterion for the iterative refinement. We present a benchmark to demonstrate the speedup obtained by using single precision representations of the sparse matrices involved. We also design an adaptive algorithm that uses the aforementioned estimator to identify when iterative refinement in single precision fails and is able to recover and solve the problem fully in double precision
Gulbinas, Gediminas. "Šiuolaikiniais maišytuvais gaminamo asfaltbetonio mišinių kokybės gerinimo galimybių analizė." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2005. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050612_224508-61143.
Duarte, Cláudia Filipa Pires. "Essays on mixed-frequency data : forecasting and unit root testing." Doctoral thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/11662.
Nas últimas décadas, OS investigadores têm tido acesso a bases de dados cada vez mais abrangentes, que incluem séries com frequências temporais mais elevadas e que são divulgadas mais atempadamente. Em contraste, algumas variáveis, nomeadamente alguns dos principais indicadores macroeconómicos, são divulgados com urn desfasamento temporal significativo e com baixa frequência. Esta situação levanta questões sobre como lidar com séries com frequências temporais diferentes, mistas. Ao longo do tempo, várias técnicas têm sido propostas. Esta tese debruça-se sobre uma técnica em particular - a abordagem MI(xed) DA{ta) S{ampling), proposta por Ghysels et al. (2004). No Capitulo 1 eu utilizo a técnica MIDAS para prever o crescimento do PIB na área do euro com base num pequcno conjunto de indicadores, cobrindo séries com diferentes frequências temporais e divulgadas com diferentes desfasamentos. Eu cornparo o desempenho de urn conjunto alargado de regressões MIDAS, utilizando a raiz quadrada do erro quadrático média de previsão e tomando como ponto de referência quer regressões autoregressivas, quer multivariadas (bridge models). A questão sobre a forma de introduzir tcrmos autoregressivos nas equações MIDAS é dirirnida. São consideradas diferentes combinações de variáveis, obtidas através da agregação de previsões ou de regressões multivariadas, assim como diferentes frequências ternporais. Os resultados sugerern que, em geral, a utilização de regressões MIDAS contribui para o aurnento da precisão das previsões. Adicionalmente, nesta tese são propostos novas testes de raízes unitárias que exploram inforrnação com frequências rnistas. Tipicamente, os testes de raízes unitárias têm baixa potência, especialrnente em amostras pequenas. Uma forma de combatcr esta dificuldade consiste em recorrer a testes que exploram informação adicional de urn regressor estacionário incluído na regressão de teste. Eu avalio se é possível melhorar 0 desempenho de alguns testes deste tipo ao explorar dados com frequêcias temporais mistas, através de regressões MIDAS. No Capitulo 2 eu proponho uma nova classe de testes da familia Dickey-Fuller (DF) com regressores adicionais de frequência temporal mista, tomando por base os testes DF com regressores adicionais (CADF) propostos por Hansen (1995) e uma versão modificada proposta por Pesavento (2006), semelhante ao filtro GLS aplicado ao teste ADF univariado em Elliott et al. (1996). Em alternativa aos testes da familia DF, Elliott and Jansson (2003) propõem urn teste de raízes unitárias viável que retém propriedades óptimas mesmo na presenc;a de variáveis deterministicas (EJ), tomando por base a versão univariada proposta por Elliott et al. (1996). No Capitulo 3 eu alargo o âmbito de aplicação destes testes de forma a incluir dados com frequência temporal mista. Dado que para implementar o teste EJ é necessário estimar modclos VAR, eu proponho urn modelo VAR-MIDAS não restrito, parcimonioso, que inclui séries de frequência temporal mista e é estimado com técnicas econométricas tradicionais. Os resultados de urn exercício de Monte Carlo indicam que os testes com dados de frequência temporal mista têrn urn desempenho em termos de potência melhor do que os testes que agregam todas as variáveis para a mcsma frequência temporal (necessariamente a frequência mais baixa). Os ganhos são robustos à dimensão da amostra, à escolha do número de desfasamentos a incluir nas regressões de teste e às frequências temporais concretas. Adicionalmente, os testes da familia EJ tendem a ter urn melhor desempenho do que os testes da familia CADF, independentemente das frequências temporais consideradas. Para ilustrar empiricamentc a utilização destes testes, analisa-se a série da taxa de desemprego nos EUA.
Over the last decades, researchers have had access to more comprehensive datasets, which are released on a more frequent and timely basis. Nevertheless, some variables, namely some key macroeconomic indicators, are released with a significant time delay and at low frequencies. This situation raises the question on how to deal with series released at different, mixed time frequencies. Over the years and for different purposes, several techniques have been put forward. This essav focuses on a particular technique - the MI(xed) DA(ta) S(ampling) framework, proposed by Ghysels et al. (2004). In Chapter 1 I use MIDAS for forecasting euro area GDP growth using a small set of selected indicators in an environment with different sampling frequencies and asynchronous releases of information. I run a horse race between a wide set of MIDAS regressions and evaluate their performance, in terms of root mean squared forecast error, against AR and quarterly bridge models. The issue on how to include autoregressive terms in MIDAS regressions is disentangled. Different combinations of variables, through forecast pooling and multi-variable regressions, and different time frequencies are also considered. The results obtained suggest that in general, using MIDAS regressions contributes to increase forecast accuracy. In addition, I propose new unit root tests that exploit mixed-frequency information. Unit root tests typically suffer from low power in small samples. To overcome this shortcoming, tests exploiting information from stationary covariates have been proposed. I assess whether it is possible to improve the power performance of some of these tests by exploiting mixed-frequency data, through the MIDAS approach. In Chapter 2 I put forward a new class of mixed-frequency covariate-augmented Dickey-Fuller (DF) tests, extending the covariate-augmented DF test (CADF test) proposed by Hansen (1995) and its modified version, similar to the GLS generalisation of the univariate ADF test in Elliott et al. (1996), proposed by Pesavento (2006). Alternatively to the CADF tests, Elliott and Jansson (2003) proposed a feasible point optimal unit root test in the presence of deterministic components (EJ test hereafter), which extended the univariate results in Elliott et al. (1996). In Chapter 3 I go one step further and include mixed-frequency data in the EJ testing framework. Given that implementing the EJ test requires estimating VAR models, in order to plug in mixed-frequency data in the test regression I propose an unconstrained, though parsimonious, stacked skip-sampled reduced-form VAR-MIDAS model, which is estimated using standard econometric techniques. The results from a Monte Carlo exercise indicate that mixed-frequency tests have better power performance than low-frequency tests. The gains are robust to the size of the sample, to the lag specification of the test regressions and to different combinations of time frequencies. Moreover, the EJ-family of tests tends to have a better power performance than the CADF-family of tests, either with low or mixed-frequency data. An empirical illustration using the US unemployment rate is presented.
Huang, Jhih-Ming, and 黃志銘. "Inexact and Mixed Precision Eigenvalue Solvers on GPU." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/73593608140877647378.
國立臺灣大學
數學研究所
102
Eigenvalue problem is one of the most crucial topics in engineering and science fields nowaday. In practice applications, the target matrix is usually large and sparse, hence solving the eigenvalue problems need huge computa- tion amount. The high efficiency is a strong demand in practice, therefore High Performance Computing, HPC, plays an important role in this topic. One important approach for getting higher performance is mixed precision design, which means it will change the operation precision during the com- putation without dropping the finial accuracy. Since single precision requires less memory storage and it may cause higher cache hit ratio, which may affect performance a lot. In addition, in some numerical operation, single precision is faster than double precision. Hence, if the original algorithm is accuracy insensitive, which means that it could lost some accuracy during the compu- tation and keep the same final accuracy, then it is suitable to be redesigned as a mixed precision type algorithm to enhance the performance. The eigen- solver we focus on exactly belongs to this type. Shift-Invert Residual Arnoldi, SIRA, algorithm is an well-known eigenvalue solver, which consists of an in- ner loop and an outer loop. The inner loop is solving a linear system, which is for searching the correction direction to help outer loop find the desired eigen-pair. The efficiency of SIRA relies on the solutions of the inner-loop linear systems. These systems can be solved in lower accuracy without down- grading the final accuracy of the target eigenvalues. By taking advantage of this algorithmic feature and the computational power of GPU, we develop a mixed precision eigensolver in this research. We develop a method called pocket method, it adaptively choosing the double or single precision to solve the linear system. Moreover, in solving the linear system, it automatically adjust the inner tolerance and timing of exiting inner loop. Pocket method has the best performance in most of our experiments.
Hsieh, Chen-Yuan, and 謝禎原. "HapticSphere: Physical Support To Enable Precision Touch Interaction in Mobile Mixed-Reality." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/8e9t49.
國立交通大學
資訊科學與工程研究所
106
This work presents HapticSphere, a wearable spherical surface enabled by bridging a finger and the HMD with a passive string. Users perceive physical support at the finger when reaching it to the surface defined by the string extent. This physical support assists users in precise touch interaction in the context of stationary and walking virtual or mixed-reality. We propose three methods of attachment of the haptic string (directly on the head or on the body), and illustrate a novel single-step calibration algorithm that supports these configurations by estimation of a grand haptic sphere, once an head-coordinated touch interaction is established. Two user studies were conducted to validate our approach and to compare the touch performance with physical support in sitting and walking situations in the context of mobile mixed-reality scenarios. The results reported that, in walking condition, touch interaction with physical support significantly outperform with the visual-only condition. There is an extend work at the end, adding string-based device to commercial product, which is suitable for long-term task, such as VR desktop.
Su, Chia-Sheng, and 蘇家陞. "Development of a Precision Irrigation Model for a Mixed Paddy Rice and Upland Crops Field." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/45145685045495707315.
國立中央大學
土木工程學系
104
In Taiwan, irrigation water accounts for the major usage in agricultural water. Recently, mixed paddy rice and upland crops fields becomes more and more popular for farmers choose to grow crops based on their individual wills. Given the situation that in Taiwan irrigation water distribution depends on manual work, and the water of irrigation and the lost from the conveyance can not be accurately calculated, the supply and demand in the field is lack of coordination. This study applies system dynamic model to establish irrigation water management model for a mixed paddy rice and upland crops field in central Taiwan. The goal is to provide precision irrigation practice allocating irrigation water in such way to minimize water loss and raise efficiency. Through precision irrigation practice for mixed paddy rice and upland crops fields, a substantial saving in irrigation water, i.e., 291 mm in terms of water depth can be realized for one season of growing vegetable in 2016. In the case of paddy field, 519 mm of water saving was estimated for a 30-days simulation on the proposed automatic control gates system in the second rice crop on 2015. Moreover, in the test site, the pumped groundwater was estimated to be 81 mm in depth, which compared to the simulated water requirement 65 mm indicates the possible eater saving being 16 mm. The study on the possible water saving for 9 scenarios provides information in management the mixed crops farming in water shortage periods.
Buonocore, Luca. "Ultimate precision for the Drell-Yan process: mixed QCDxQED(EW) corrections, final state radiation and power suppressed contributions." Tesi di dottorato, 2020. http://www.fedoa.unina.it/13156/1/luca_buonocore_32.pdf.
Kubínová, Marie. "Numerické metody pro řešení diskrétních inverzních úloh." Doctoral thesis, 2018. http://www.nusl.cz/ntk/nusl-392433.
BLAHOUT, Jaroslav. "Vliv jednotlivých komponent směsných krmných dávek u krmných míchacích vozů (bez vybírací frézy) na přesnost nakládek." Master's thesis, 2016. http://www.nusl.cz/ntk/nusl-381151.