Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 106 for “"Divide and conquer"”.
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Autotuning divide-and-conquer matrix-vector multiplication
Divide and conquer is an important concept in computer science. It is used ubiquitously to simplify and speed up programs. However, it needs to be optimized, with respect to parameter settings for example, in order to achieve the best performance. The problem boils down to searching for the best …
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A "divide-and-conquer" strategy for NDE signal inversion in gas transmission pipelines
… remediation decisions are made. The accuracy and confidence of the signal inversion results therefore play a key role in evaluating the effectiveness of the NDE procedure. Conventional NDE signal inversion algorithms that employ artificial neural networks treat all geometric regions of the NDE …
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Selective solidarity: Russia's divide and conquer strategy and the impact on EU energy security
… energy flow gives Russia powerful leverage and Russia continues to use this to its geo-political advantage. Although the Russian economy is heavily dependent on revenue from EU consumers, this has not prevented energy monopolies from becoming involved in diplomacy. Since President Vladimir …
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"An Investigation of Decomposed and Holistic Judgments in Multiattribute Decision Making: Generalizing the ""Divide and Conquer"" Principle"
… validity (e.g. the agreement between decomposed and holistic strategies), the temporal stability and the external validity (the agreement between a decision strategy and an objective criterion) for decomposed and holistic judgments from two popular multi-criteria decision making techniques, …
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Provably efficient randomized work stealing with first-class parallel loops
… can be executed independently in any order and thus contribute to high parallelism. Techniques such as divide-and-conquer and lazy binary splitting have proven to be efficient in theory and/or in practice. However, these approaches can potentially be improved in terms of lower number of …
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Portable and productive high-performance computing
Performance portability of computer programs, and programmer productivity in writing them are key expectations in software engineering. These expectations lead to the following questions: Can programmers write code once, and execute it at optimal speed on any machine configuration? Can programmers …
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Combining search strategies for distributed constraint satisfaction.
… meeting scheduling, mobile frequency allocation and resource allocation can be solved using multi-agent paradigms. Distributed constraint satisfaction problems (DisCSPs) is a framework for describing such problems in terms of related subproblems, called a complex local problem (CLP), which are …
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Improving the Performance of Parallel Loops in OpenCilk
… scheduling must achieve low scheduling overheads and multidimensional locality in nested loops. This thesis explores both challenges and contributes an extension to randomized work-stealing for first-class loop support that reduces scheduling overheads. Randomized work-stealing schedulers …
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Quantum Algorithms For String Problems
… processing problems: Longest Common Substring and Lexicographically Minimal String Rotation. Specifically, we show that: - Longest Common Substring can be solved by a quantum algorithm in Õ(n²⸍³) time, improving upon the Õ(n⁵⸍⁶)-time algorithm by Le Gall and Seddighin (2022). Moreover, given a …
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New statistical perspectives on efficient Big Data algorithms for high-dimensional Bayesian regression and model selection
… containing a large number of observations. Standard algorithms be prohibitively computationally demanding on large $n$ datasets, and we propose and analyse new computational methods for model fitting and selection. We explore three different generic strategies for tall datasets. Divide and …
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A virtual machine approach to parallel debugging
… to be difficult. The increased complexity and non determinism of parallel programs makes it even more difficult. It is one of the reasons that parallel machines are not widely used for computationally intensive applications even though recent progress on VLSI technology has significantly …
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New Parallel Algorithms for Planarity Testing
… in which no edges cross) have special properties and are often used in applications such as circuit design or transportation networks. While many linear work implementations of planarity testing algorithms exist, to our best knowledge, there is no practical implementation of a parallel planarity …
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Precision Aggregated Local Models
… larger data sets due to cubic scaling of flops and quadratic storage involved in working with covariance matrices. Remedies in recent literature focus on divide-and-conquer, e.g., partitioning into sub-problems and inducing functional (and thus computational) independence. Such approximations …
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Large-scale Geometric Data Decomposition, Processing and Structured Mesh Generation
Mesh generation is a fundamental and critical problem in geometric data modeling and processing. In most scientific and engineering tasks that involve numerical computations and simulations on 2D/3D regions or on curved geometric objects, discretizing or approximating the geometric data using a …
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Systematic conformational search with constraint satisfaction
… is a high scientific priority for biochemists and for the pharmaceutical industry. This thesis describes a systematic method for conformational search, an application of the method to determining the structure of the formyl-Met-Leu-Phe-OH (fMLF)peptide by solid-state NMR spectroscopy, and a …
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Analysis of recursive cache-adaptive algorithms
The performance and behavior of caches is becoming increasingly important to the overall performance of systems. As a result, there has been extensive study of caching in theoretical computer science. The traditionally studied model was the external-memory model [AV88]. In this model cache misses …
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Variational Inference Using Approximate Likelihood Under the Coalescent With Recombination
Coalescent methods are proven and powerful tools for population genetics, phylogenetics, epidemiology, and other fields. The multispecies coalescent (MSC) model has been widely employed by phylogenetic algorithms to construct the species tree while accounting for incomplete lineage sorting (ILS). …
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Branch decompositions and their applications
… method to solve these problems is by branch and bound while another method is by graph decompositions. In the 1980's, Robertson and Seymour conceived of two new ways to decompose the graph in order to solve these problems. These ingenious ideas were only by-products of their work proving …
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An Approach For Scalable First-Order Rule Learning On Twitter Data
Scalable Rule Learning (SRLearn) is a scalable divide-and-conquer approach with graph-based modeling of social media data, to scale up first-order rule learning through Markov Logic Networks on a commodity cluster on large scale Twitter data. SRLearn takes advantage of distributed systems to …
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