Relevant bibliographies by topics / GPU Processing / Dissertations / Theses
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Dissertations / Theses on the topic 'GPU Processing'

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Published: 4 June 2021
Last updated: 6 February 2022

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1

Yanggratoke, Rerngvit. "GPU Network Processing." Thesis, KTH, Telekommunikationssystem, TSLab, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-103694.

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Networking technology is connecting more and more people around the world. It has become an essential part of our daily life. For this connectivity to be seamless, networks need to be fast. Nonetheless, rapid growth in network traffic and variety of communication protocols overwhelms the Central Processing Units (CPUs) processing packets in the networks. Existing solutions to this problem such as ASIC, FPGA, NPU, and TOE are not cost effective and easy to manage because they require special hardware and custom configurations. This thesis approaches the problem differently by offloading the net
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Johansen, Owe. "Seismic Shot Processing on GPU." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9956.

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<p>Today’s petroleum industry demand an ever increasing amount of compu- tational resources. Seismic processing applications in use by these types of companies have generally been using large clusters of compute nodes, whose only computing resource has been the CPU. However, using Graphics Pro- cessing Units (GPU) for general purpose programming is these days becoming increasingly more popular in the high performance computing area. In 2007, NVIDIA corporation launched their framework for developing GPU utilizing computational algorithms, known as the Compute Unied Device Architec- ture (CUDA)
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Ekstam, Ljusegren Hannes, and Hannes Jonsson. "Parallelizing Digital Signal Processing for GPU." Thesis, Linköpings universitet, Programvara och system, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167189.

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Because of the increasing importance of signal processing in today's society, there is a need to easily experiment with new ways to process signals. Usually, fast-performing digital signal processing is done with special-purpose hardware that are difficult to develop for. GPUs pose an alternative for fast performing digital signal processing. The work in this thesis is an analysis and implementation of a GPU version of a digital signal processing chain provided by SAAB. Through an iterative process of development and testing, a final implementation was achieved. Two benchmarks, both comprised
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Gjermundsen, Aleksander. "CPU and GPU Co-processing for Sound." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11794.

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When using voice communications, one of the problematic phenomena that can occur, is participants hearing an echo of their own voice. Acoustic echo cancellation (AEC) is used to remove this echo, but can be computationally demanding.The recent OpenCL standard allows high-level programs to be run on both multi-core CPUs, as well as Graphics Processing Units (GPUs) and custom accelerators. This opens up new possibilities for offloading computations, which is especially important for real-time applications. Although many algorithms for image- and video-processing have been studied on the GPU, aud
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Karlsson, Per. "A GPU-based framework for efficient image processing." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-112093.

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This thesis tries to answer how to design a framework for image processing on the GPU, supporting the common environments OpenGL GLSL, OpenCL and CUDA. An generalized view of GPU image processing is presented. The framework is called gpuip and is implemented in C++ but also wrapped with Python-bindings. The framework is cross-platform and works for Windows, Mac OSX and Unix operating systems. The thesis also involves the work of creating two executable programs that uses the gpuip-framework. One of the programs has a graphical user interface and the other program is command-line only. Both pro
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Dvořák, Jakub. "Streaming Ray Tracer na GPU." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-236008.

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Current consumer GPUs can be used as high performance stream processors and are a tempting platform to be used to implement raytracing. In this paper I briefly present raytracing principles and methods used to accelerate it, modern GPUs programmable pipeline and examples of its use. I describe stream processing in general and available interfaces enabling the usage of GPU as stream processor. Then I present my GPU raytracer implementation, used algorithms and experiments I have made.
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Tokdemir, Serpil. "Digital compression on GPU." unrestricted, 2006. http://etd.gsu.edu/theses/available/etd-12012006-154433/.

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Thesis (M.S.)--Georgia State University, 2006.<br>Title from dissertation title page. Saeid Belkasim, committee chair; Ying Zhu, A.P. Preethy, committee members. Electronic text (90 p. : ill. (some col.)). Description based on contents viewed May 2, 2007. Includes bibliographical references (p. 78-81).
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Mensmann, Jörg, Timo Ropinski, and Klaus Hinrichs. "An Advanced Volume Raycasting Technique using GPU Stream Processing." University of Münster, Germany, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-92874.

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GPU-based raycasting is the state-of-the-art rendering technique for interactive volume visualization. The ray traversal is usually implemented in a fragment shader, utilizing the hardware in a way that was not originally intended. New programming interfaces for stream processing, such as CUDA, support a more general programming model and the use of additional device features, which are not accessible through traditional shader programming. In this paper we propose a slab-based raycasting technique that is modeled specifically to use these features to accelerate volume rendering. This techniqu
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Fathi, Salmi Meisam. "Processing Big Data in Main Memory and on GPU." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1451992820.

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10

Zhao, Kaiyong. "GPU accelerated sequence alignment /Zhao Kaiyong." HKBU Institutional Repository, 2016. https://repository.hkbu.edu.hk/etd_oa/378.

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DNA sequence alignment is a fundamental task in gene information processing, which is about searching the location of a string (usually based on newly collected DNA data) in the existing huge DNA sequence databases. Due to the huge amount of newly generated DNA data and the complexity of approximate string match, sequence alignment becomes a time-consuming process. Hence how to reduce the alignment time becomes a significant research problem. Some algorithms of string alignment based on HASH comparison, suffix array and BWT, which have been proposed for DNA sequence alignment. Although these a
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Nottingham, Alastair. "GPF : a framework for general packet classification on GPU co-processors." Thesis, Rhodes University, 2012. http://hdl.handle.net/10962/d1006662.

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This thesis explores the design and experimental implementation of GPF, a novel protocol-independent, multi-match packet classification framework. This framework is targeted and optimised for flexible, efficient execution on NVIDIA GPU platforms through the CUDA API, but should not be difficult to port to other platforms, such as OpenCL, in the future. GPF was conceived and developed in order to accelerate classification of large packet capture files, such as those collected by Network Telescopes. It uses a multiphase SIMD classification process which exploits both the parallelism of packet se
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Flannery, Rebecca Lynn. "A hybrid fluid simulation on the Graphics Processing Unit (GPU)." Texas A&M University, 2008. http://hdl.handle.net/1969.1/85974.

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This thesis presents a method to implement a hybrid particle/grid uid simulation on graphics hardware. The goal is to speed up the simulation by exploiting the parallelism of the graphics processing unit, or GPU. The Fluid Implicit Particle method is adapted to the programming style of the GPU. The methods were implemented on a current generation graphics card. The GPU based program exhibited a small speedup over its CPU based counterpart.
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Baravdish, Gabriel. "GPU Accelerated Light Field Compression." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150558.

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This thesis presents a GPU accelerated method to compress light field or light field videos. The implementation is based on an earlier work of a full light field compression framework. The large amount of data storage by capturing light fields is a challenge to compress and we seek to accelerate the encoding part. We compress by projecting each data point onto a set of dictionaries and seek a sparse representation with the least error. An optimized greedy algorithm to suit computations on the GPU is presented. We benefit of the algorithm outline by encoding the data segmentally in parallel for
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Cai, Bo. "Scattered Data Visualization Using GPU." University of Akron / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=akron1428077896.

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Wu, Haicheng. "Acceleration and execution of relational queries using general purpose graphics processing unit (GPGPU)." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54405.

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This thesis first maps the relational computation onto Graphics Processing Units (GPU)s by designing a series of tools and then explores the different opportunities of reducing the limitation brought by the memory hierarchy across the CPU and GPU system. First, a complete end-to-end compiler and runtime infrastructure, Red Fox, is proposed. The evaluation on the full set of industry standard TPC-H queries on a single node GPU shows on average Red Fox is 11.20x faster compared with a commercial database system on a state of art CPU machine. Second, a new compiler technique called kernel fusion
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Eklund, Anders, Paul Dufort, Daniel Forsberg, and Stephen LaConte. "Medical Image Processing on the GPU : Past, Present and Future." Linköpings universitet, Medicinsk informatik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93673.

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Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, hist
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Cyrus, Sam. "Fast Computation on Processing Data Warehousing Queries on GPU Devices." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6214.

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Current database management systems use Graphic Processing Units (GPUs) as dedicated accelerators to process each individual query, which results in underutilization of GPU. When a single query data warehousing workload was run on an open source GPU query engine, the utilization of main GPU resources was found to be less than 25%. The low utilization then leads to low system throughput. To resolve this problem, this paper suggests a way to transfer all of the desired data into the global memory of GPU and keep it until all queries are executed as one batch. The PCIe transfer time from CPU to G
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Vinjarapu, Saranya S. "GPU Based Scattered Data Modeling." University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1335297259.

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Appelgren, Filip, and Måns Ekelund. "Performance Evaluation of a Signal Processing Algorithm with General-Purpose Computing on a Graphics Processing Unit." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-253816.

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Graphics Processing Units (GPU) are increasingly being used for general-purpose programming, instead of their traditional graphical tasks. This is because of their raw computational power, which in some cases give them an advantage over the traditionally used Central Processing Unit (CPU). This thesis therefore sets out to identify the performance of a GPU in a correlation algorithm, and what parameters have the greatest effect on GPU performance. The method used for determining performance was quantitative, utilizing a clock library in C++ to measure performance of the algorithm as problem si
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Pettersson, Jimmy, and Ian Wainwright. "Radar Signal Processing with Graphics Processors (GPUS)." Thesis, Uppsala University, Division of Scientific Computing, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-114003.

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Smith, Michael Shawn. "Performance Analysis of Hybrid CPU/GPU Environments." PDXScholar, 2010. https://pdxscholar.library.pdx.edu/open_access_etds/300.

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We present two metrics to assist the performance analyst to gain a unified view of application performance in a hybrid environment: GPU Computation Percentage and GPU Load Balance. We analyze the metrics using a matrix multiplication benchmark suite and a real scientific application. We also extend an experiment management system to support GPU performance data and to calculate and store our GPU Computation Percentage and GPU Load Balance metrics.
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Iwaniec, Michel. "Rendering for Microlithography on GPU Hardware." Thesis, Linköping University, Department of Science and Technology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11800.

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<p>Over the last decades, integrated circuits have changed our everyday lives in a number of ways. Many common devices today taken for granted would not have been possible without this industrial revolution.</p><p>Central to the manufacturing of integrated circuits is the photomask used to expose the wafers. Additionally, such photomasks are also used for manufacturing of flat screen displays. Microlithography, the manufacturing technique of such photomasks, requires complex electronics equipment that excels in both speed and fidelity. Manufacture of such equipment requires competence in virtu
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Segura, Salvador Albert. "High-performance and energy-efficient irregular graph processing on GPU architectures." Doctoral thesis, Universitat Politècnica de Catalunya, 2021. http://hdl.handle.net/10803/671449.

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Graph processing is an established and prominent domain that is the foundation of new emerging applications in areas such as Data Analytics and Machine Learning, empowering applications such as road navigation, social networks and automatic speech recognition. The large amount of data employed in these domains requires high throughput architectures such as GPGPU. Although the processing of large graph-based workloads exhibits a high degree of parallelism, memory access patterns tend to be highly irregular, leading to poor efficiency due to memory divergence.In order to ameliorate these issues,
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Ohmer, Julius Fabian. "Computer vision applications on graphics processing units." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16463/.

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Over the last few years, commodity Graphics Processing Units (GPUs) have evolved from fixed graphics pipeline processors into more flexible and powerful data-parallel processors. These stream processors are capable of sustaining computation rates of greater than ten times that of a single-core CPU. GPUs are inexpensive and are becoming ubiquitous in a wide variety of computer architectures including desktop and laptop computers, PDAs and cell phones. This research works investigates possible ways to use modern GPUs for real-time computer vision and pattern classification tasks. Special atte
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Keith, Tūreiti. "A General-Purpose GPU Reservoir Computer." Thesis, University of Canterbury. Department of Electrical & Computer Engineering, 2013. http://hdl.handle.net/10092/7617.

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The reservoir computer comprises a reservoir of possibly non-linear, possibly chaotic dynamics. By perturbing and taking outputs from this reservoir, its dynamics may be harnessed to compute complex problems at “the edge of chaos”. One of the first forms of reservoir computer, the Echo State Network (ESN), is a form of artificial neural network that builds its reservoir from a large and sparsely connected recurrent neural network (RNN). The ESN was initially introduced as an innovative solution to train RNNs which, up until that point, was a notoriously difficult task. The innovation of the ES
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Enfedaque, Montes Pablo. "GPU Architectures for Wavelet-based Image Coding Acceleration." Doctoral thesis, Universitat Autònoma de Barcelona, 2017. http://hdl.handle.net/10803/405310.

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Els sistemes de codificació d'imatges moderns utilitzen tècniques amb alts requirements de comput per tal d'aconseguir comprimir imatges de manera eficient. Les aplicacions que fan us d'aquests codecs sovint tenen necesitats de processament en temps real. És habitual en aquests escenaris fer ús de hardware especialitzat com, per exemple, Field-Programmable Gate Arrays (FPGAs) o Applications-Specific Integrated Circuits (ASICs). No obstant, les GPUs, amb la seva arquitectura altament paral·lela orientada a rendiment, representen una alternativa atractiva en comparació al hardware especialitzat.
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Zhang, Chenggang, and 张呈刚. "Run-time loop parallelization with efficient dependency checking on GPU-accelerated platforms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47167658.

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General-Purpose computing on Graphics Processing Units (GPGPU) has attracted a lot of attention recently. Exciting results have been reported in using GPUs to accelerate applications in various domains such as scientific simulations, data mining, bio-informatics and computational finance. However, up to now GPUs can only accelerate data-parallel loops with statically analyzable parallelism. Loops with dynamic parallelism (e.g., with array accesses through subscripted subscripts), an important pattern in many general-purpose applications, cannot be parallelized on GPUs using existing technolog
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He, Jintai. "MULTIPLE SEQUENCES ALIGNMENT FOR PHYLOGENETIC TREE CONSTRUCTION USING GRAPHICS PROCESSING UNITS." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1674095441&sid=1&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Thesis (M.S.)--Southern Illinois University Carbondale, 2008.<br>"Department of Computer Science." Keywords: GPU computing, Sequence alignment. Includes bibliographical references (p. 34). Also available online.
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Sundin, Patricia. "Adaptation of algorithms for underwater sonar data processing to GPU-based systems." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-94023.

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In this master thesis, algorithms for acoustic simulations in underwater environments are ported for GPU processing. The GPU parallel computing platforms used are CUDA, OpenCL and SkePU. The purpose of this master thesis is to adapt and evaluate the ported algorithms' performance on two modern NVIDIA GPUs, Tesla K20 and Quadro K5000. Several optimizations, described in existing literature for GPU processing (e.g. usage of shared memory, coalesced memory accesses), are implemented and multiple versions of each algorithm are created to study their trade-offs. Evaluation on two GPUs showed that d
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Macenauer, Pavel. "Detekce objektů na GPU." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234942.

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This thesis addresses the topic of object detection on graphics processing units. As a part of it, a system for object detection using NVIDIA CUDA was designed and implemented, allowing for realtime video object detection and bulk processing. Its contribution is mainly to study the options of NVIDIA CUDA technology and current graphics processing units for object detection acceleration. Also parallel algorithms for object detection are discussed and suggested.
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Gruslys, Audrūnas. "Development and applications of GPU based medical image registration." Thesis, University of Cambridge, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708078.

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Han, Guodong, and 韩国栋. "Profile-guided loop parallelization and co-scheduling on GPU-based heterogeneous many-core architectures." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50534257.

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The GPU-based heterogeneous architectures (e.g., Tianhe-1A, Nebulae), composing multi-core CPU and GPU, have drawn increasing adoptions and are becoming the norm of supercomputing as they are cost-effective and power-efficient. However, programming such heterogeneous architectures still requires significant effort from application developers using sophisticated GPU programming languages such as CUDA and OpenCL. Although some automatic parallelization tools utilizing static analysis could ease the programming efforts, this approach could only parallelize loops 100% free of inter-iteration dep
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Wang, Kaibo. "Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1447685368.

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Xiao, Shucai. "Generalizing the Utility of Graphics Processing Units in Large-Scale Heterogeneous Computing Systems." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/51845.

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Today, heterogeneous computing systems are widely used to meet the increasing demand for high-performance computing. These systems commonly use powerful and energy-efficient accelerators to augment general-purpose processors (i.e., CPUs). The graphic processing unit (GPU) is one such accelerator. Originally designed solely for graphics processing, GPUs have evolved into programmable processors that can deliver massive parallel processing power for general-purpose applications. Using SIMD (Single Instruction Multiple Data) based components as building units; the current GPU architecture is we
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Callanan, Gareth Mitchell. "A GPU based X-Engine for the MeerKAT Radio Telescope." Master's thesis, University of Cape Town, 2020. http://hdl.handle.net/11427/32531.

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The correlator is a key component of the digital backend of a modern radio telescope array. The 64 antenna MeerKAT telescope has an FX architecture correlator consisting of 64 F-Engines and 256 X-Engines. These F- and X-Engines are all hosted on 128 custom designed FPGA processing boards. This custom board is known as a SKARAB. One SKARAB X-Engine board hosts four logical X-Engines. This SKARAB ingests data at 27.2 Gbps over a 40 GbE connection. It correlates this data in real time. GPU technology has improved significantly since SKARAB was designed. GPUs are now becoming viable alternatives t
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Mei, Xinxin. "Energy conservation techniques for GPU computing." HKBU Institutional Repository, 2016. https://repository.hkbu.edu.hk/etd_oa/298.

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The emerging general purpose graphics processing units (GPGPU) computing has tremendously speeded up a great variety of commercial and scientific applications. The GPUs have become prevalent accelerators in current high performance clusters. Though the computational capacity per Watt of the GPUs is much higher than that of the CPUs, the hybrid GPU clusters still consume enormous power. To conserve energy on this kind of clusters is of critical significance. In this thesis, we seek energy conservative computing on the GPU accelerated servers. We introduce our studies as follows. First, we disse
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Persson, Daniel. "Testing Complex Data-structures on General Purpose Graphics Processing Units." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3614.

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This thesis is about general purpose computing on the graphics processor. The reason why this is important is because of the performance advantages that can be achieved in ordinary applications by using the GPUs programmability and performance. The problem investigated is the use of a complex data-structure, namely linked lists, and what their possible benefits are when run on the GPU. I also wanted to investigate if it was viable to implement a complex data-structure on a GPU. Implementations was made of the linked list both on the GPU and on the CPU and then measurements of the performance o
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McLaughlin, Adam Thomas. "Power-constrained performance optimization of GPU graph traversal." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50209.

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Graph traversal represents an important class of graph algorithms that is the nucleus of many large scale graph analytics applications. While improving the performance of such algorithms using GPUs has received attention, understanding and managing performance under power constraints has not yet received similar attention. This thesis first explores the power and performance characteristics of breadth first search (BFS) via measurements on a commodity GPU. We utilize this analysis to address the problem of minimizing execution time below a predefined power limit or power cap exposing key rela
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Tarassu, Jonas. "GPU-Accelerated Frame Pre-Processing for Use in Low Latency Computer Vision Applications." Thesis, Linköpings universitet, Informationskodning, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-142019.

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The attention for low latency computer vision and video processing applications are growing for every year, not least the VR and AR applications. In this thesis the Contrast Limited Adaptive Histogram Equalization (CLAHE) and Radial Dis- tortion algorithms are implemented using both CUDA and OpenCL to determine whether these type of algorithms are suitable for implementations aimed to run at GPUs when low latency is of utmost importance. The result is an implemen- tation of the block versions of the CLAHE algorithm which utilizes the built in interpolation hardware that resides on the GPU to r
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Kilpatrick, Stephen, Philip M. Westhart, and Ben A. Abbott. "AN OPEN, SCALABLE APPROACH TO EFFICIENT DATA PROCESSING." International Foundation for Telemetering, 2016. http://hdl.handle.net/10150/624226.

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The growth of network-based systems in flight test will present performance problems within the community. Legacy instrumentation systems are not capable of meeting the high-bandwidth, low latency data processing requirements of these next generation data acquisition systems. Ongoing research at Southwest Research Institute is exploring the use of a variety of commodity components, such as Graphics Processing Units (GPUs) and multicore Central Processing Units (CPUs), in ways that can be applied to both the small embedded components as well as the larger ground systems. This paper will e
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Löw, Joakim. "Ray Tracing Bézier Surfaces on GPU." Thesis, Linköping University, Department of Mathematics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5476.

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<p>In this report, we show how to implement direct ray tracing of B´ezier surfaces on graphics processing units (GPUs), in particular bicubic rectangular Bézier surfaces and nonparametric cubic Bézier triangles. We use Newton’s method for the rectangular case and show how to use this method to find the ray-surface intersection. For Newton’s method to work we must build a spatial partitioning hierarchy around each surface patch, and in general, hierarchies are essential to speed up the process of ray tracing. We have chosen to use bounding box hierarchies and show how to implement stackless tra
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Larsson, Jonas. "A Case Study of Parallel Bilateral Filtering on the GPU." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-29589.

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Smoothing and noise reduction of images is often an important first step in image processing applications. Simple image smoothing algorithms like the Gaussian filter have the unfortunate side effect of blurring the image which could obfuscate important information and have a negative impact on the following applications. The bilateral filter is a well-used non-linear smoothing algorithm that seeks to preserve edges and contours while removing noise. The bilateral filter comes at a heavy cost in computational speed, especially when used on larger images, since the algorithm does a greater amount of
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Le, Jianwei. "A GPU-based framework for real-time rendering of open water phenomena /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?CSED%202008%20LE.

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Wozniak, Jan. "Design and Performance Analysis of Parallel Processing of SRTP Packets." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236203.

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Šifrování multimediálních datových přenosů v reálném čase je jednou z úloh telekomunikační infrastruktury pro dosažení nezbytné úrovně zabezpečení. Rychlost provedení šifrovacího algoritmu může hrát klíčovou roli ve velikosti zpoždění jednotlivých paketů a proto je tento úkol zajímavým z hlediska optimalizačních metod. Tato práce se zaměřuje na možnosti paralelizace zpracování SRTP pro účely telefonní ústředny s využitím OpenCL frameworku a následnou analýzu potenciálního zlepšení.
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45

Scogland, Thomas R. "Runtime Adaptation for Autonomic Heterogeneous Computing." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/71315.

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Heterogeneity is increasing across all levels of computing, with the rise of accelerators such as GPUs, FPGAs, and other coprocessors into everything from cell phones to supercomputers. More quietly it is increasing with the rise of NUMA systems, hierarchical caching, OS noise, and a myriad of other factors. As heterogeneity becomes a fact of life, efficiently managing heterogeneous compute resources is becoming a critical, and ever more complex, task. The focus of this dissertation is to lay the foundation for an autonomic system for heterogeneous computing, employing runtime adaptation to im
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Chen, Ke. "Améliorer la performance des processeurs par l'extration dynamique du parallélisme d'instructions." Perpignan, 2012. http://www.theses.fr/2012PERP1084.

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Cette thèse étudie le parallélisme d’instructions présent dans les applications et la possibilité de l’exploiter au sein d’un processeur adapté. Les expériences faites avec l’outil de mesure PerPI conçu au sein de notre laboratoire, et dont les résultats sont rapportés dans ce mémoire, montrent que le parallélisme d’instructions n’est élevé et régulièrement réparti tout au long de l’exécution qu’en étendant le mécanisme de renommage habituellement employé. Celui-ci doit pouvoir renommer les registres et la mémoire au sein d’un espace unique et propager les constantes le long des récurrences. C
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Sidiropoulos, Konstantinos. "Pattern recognition systems design on parallel GPU architectures for breast lesions characterisation employing multimodality images." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/9190.

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The aim of this research was to address the computational complexity in designing multimodality Computer-Aided Diagnosis (CAD) systems for characterising breast lesions, by harnessing the general purpose computational potential of consumer-level Graphics Processing Units (GPUs) through parallel programming methods. The complexity in designing such systems lies on the increased dimensionality of the problem, due to the multiple imaging modalities involved, on the inherent complexity of optimal design methods for securing high precision, and on assessing the performance of the design prior to de
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Sörman, Torbjörn. "Comparison of Technologies for General-Purpose Computing on Graphics Processing Units." Thesis, Linköpings universitet, Informationskodning, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-125882.

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The computational capacity of graphics cards for general-purpose computinghave progressed fast over the last decade. A major reason is computational heavycomputer games, where standard of performance and high quality graphics constantlyrise. Another reason is better suitable technologies for programming thegraphics cards. Combined, the product is high raw performance devices andmeans to access that performance. This thesis investigates some of the currenttechnologies for general-purpose computing on graphics processing units. Technologiesare primarily compared by means of benchmarking performa
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Bačík, Ladislav. "Využití GPU pro akcelerované zpracování obrazu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235888.

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This master thesis deals with modern technologies in graphic hardware and using their for general purpose computing. It is primary focused on architecture of unified processors and algorithm implementation via CUDA programming interface. Thesis base is to choose suited algorithm for GPU horsepower demonstration. Main aim of this work is implementation of multiplatform library offering algorithms for discrete volumetric data vectorization. For this purpose was chosen algorithm Marching cubes that is able to find surface of processed object. In created library will be contained algorithm runnabl
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Akhmedov, Iliiazbek. "Parallelization of Push-based System for Molecular Simulation Data Analysis with GPU." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6448.

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Modern simulation systems generate big amount of data, which consequently has to be analyzed in a timely fashion. Traditional database management systems follow principle of pulling the needed data, processing it, and then returning the results. This approach is then optimized by means of caching, storing in different structures, or doing some sacrifices on precision of the results to make it faster. When it comes to the point of doing various queries that require analysis of the whole data, this design has the following disadvantages: considerable overhead on traditional disk random I/O frame
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