Master thesis parallel computing

The Master of Science with a major in Computer Science is designed to prepare graduate professionals who can apply the necessary knowledge of computing to information requirements of organizations in business, government, industry and education. The program provides for the education of individuals who will develop, maintain, or manage complex computer-based information systems. The program provides the experienced professional with up-to-date specialized knowledge while developing those analytical skills necessary to stay abreast of the changing field of computing. Please Note: Applicants who wish to apply for a different program will be required to submit a new application.
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Master Thesis Parallel Computing

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Computing (COMP) | Bulletin | Marquette University

Font Size: a A A. Finite element analysis is a kind of numerical analyses widely used in modern engineeringfields like physics, aviation, ship design, architecture, etc. Finite element solvers, e. High performance computing HPC , as one of the frontiers ofthe development of computer architecture, have played an important role in major stateissues such as national economy, social construction and researches on big data analyses. It has become an important issue for engineering domain, academic community as well ascomputer science field to study how HPC can be applied to all fields, how the research onfinite element can bring new insights to problem solutions and how to improve theefficiency and accuracy of complicated finite element computing in a context of big data. For the issues mentioned above, we have designed and implemented a parallelcomputing platform based on a finite element solver named Calculix. Our platform enablesmodeling, analysis and computing of the data entity in real engineering fields.
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IEK focuses on the optimal design and operation of integrated, decentralized energy systems with a high share of renewable energy. Computer simulation and numerical optimization are our essential tools to arrive at efficient, reliable and cost-effective solutions. We contribute both to the development of mathematical models and to the development of improved simulation methods and optimization algorithms. Our methods and software-tools are validated against operating data of real systems.
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The question was, if and how the GPU on such devices can be used to speed up certain algorithms especially in the fields of image processing. This thesis studies how certain popular algorithms in the field of image and audio processing can be accelerated on mobile devices by means of parallel execution on their graphics processing unit GPU. Several technologies with which this can be achieved are compared in terms of possible performance improvements, hardware and software support, as well as limitations of their programming model and functionality. The results of this research are applied in a practical project, consisting of performance improvements for marker detection in an Augmented Reality application for mobile devices.
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