Searched for: contributor%3A%22Al-Ars%2C+Zaid+%28mentor%29%22
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Berkers, Martijn (author)
The application of accelerators in HPC applications has seen enormous growth in the last decade. In the field of HPC demands on throughput are steadily growing. <br/>Not all of the algorithms used have a clear HW architecture which performs the best. Our work explores the performance of different HW architectures in solving a convex optimization...
master thesis 2020
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Feenstra, Bastiaan (author)
In this thesis we explore the acceleration of sorting algorithms on FPGAs using high bandwidth memory (HBM). The target application is an FPGA as an accelerator in an OpenCAPI enabled system, that enables the accelerator to access main memory of the host at a bandwidth of 25 GB/s for either read or write. We explore under what read and write...
master thesis 2020
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Tuna, Ozan Dogu (author)
This thesis project achieves designing and comparing two parallel implementations for exhaustive grid search along a large model space to find the optimum mapping model for overlay predictions used in ASML lithography machines. The search algorithm leads to an effectively intractable problem as long as sequential implementation is concerned, but...
master thesis 2019
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Ritsma, Folkert (author)
Performance of set based fault detection is highly dependent on the complexity of the set bounding methods used to bound the healthy residual set. Existing methods achieve robust performance with complex set bounding that narrowly define healthy system behavior, yet at the cost of higher computation times. In this thesis a major improvement is...
master thesis 2019
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Kulkarni, Rujuta (author)
The Smith Waterman algorithm is used to perform local alignment on biological sequences by calculating a similarity matrix. This process is computation-intensive. Only the elements along the minor diagonal of the matrix can be calculated in parallel, due to the nature of dependencies present in the algorithm. In the past, CPUs, GPUs and FPGAs...
master thesis 2019
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de Haan, Erwin (author)
Despite its advantages in performance and control, hardware design is mainly bottlenecked by high design complexity and long development time. This thesis explores the use of domain specific languages for high-level synthesis (HLS) of hardware data filters and transformations.<br/>The main goal of this thesis’ prototype is automating the...
master thesis 2019
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Lévy, Jonathan (author)
DNA aligning is a compute-intensive and time-consuming task required for all further DNA processing. It consists in finding for each DNA string from a sample its location in a reference genome. Usual techniques for short reads (hundreds of bases) involve seed-extension, where a small matching seed is found with quick search through FM-index and...
master thesis 2019
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Noordsij, Lennart (author)
Data movement has been long identified as the biggest challenge facing modern computer systems designers. To tackle this challenge, many novel data compression algorithms have been developed. These compression algorithms can be embedded into bandwidth-bound applications to reduce their memory traffic volume. As a result, data decompression, in...
master thesis 2019
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Miedema, Rene (author)
In the field of computational neuroscience, complex mathematical models are used to replicate brain behavior with the goal of understanding the biological processes involved. The simulation of such models are computationally expensive and therefore, in recent years, high-performance computing systems have been identified as a possible solution...
master thesis 2019
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Qiu, Tongdong (author)
Third generation sequencing machines produce reads with tens of thousands of base pairs.<br/>To perform de novo assembly, all reads must be compared with every other read to find overlaps.<br/>Finding overlaps with the optimal Smith-Waterman is not feasible, since the complexity of Smith-Waterman is quadratic with the length of the reads.<br/...
master thesis 2018
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Helmiriawan, Helmi (author)
Modern refineries typically use a high number of sensors that generate an enormous amount of data about the condition of the plants. This generated data can be used to perform predictive maintenance, an approach to predict impending failures and mitigate downtime in refineries. This research analyzes the scalability of machine learning methods...
master thesis 2018
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Guledal Lakshamana, Prashanth (author)
Processor architecture is continuously evolving. As the trend predicted by Moore's law is nearing its end, the focus of designing processors has shifted from high-frequency single-core systems to the medium frequency multicore system to a relatively lower frequency many-cores system, in the hope of extracting more performance while keeping power...
master thesis 2018
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Plaisant van der Wal, Renzo (author)
Machine learning methods are explored in an attempt to achieve better predictive performance than the legacy rule-based fraud detection systems that are currently used to detect fraudulent car insurance claims. There are two key principles that lead the exploration of machine learning techniques and algorithms in this thesis, namely, the...
master thesis 2018
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Lu, Yun (author)
In this work, a possible solution to allow for scalable MATLAB deployment on big data clusters through Spark without using the official MATLAB toolbox is introduced. Other possible solutions that can be used for accelerating existing MATLAB code including calling modules written by Graphics Processing Unit (GPU) and Python Pool with...
master thesis 2018
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Betting, Jan-Harm (author)
The movement of whiskers in head-fixed mice is of high interest for neurological research, as it allows scientists to learn more about learning processes during active touch. However, manual tracking of whiskers in thousands of frames is not feasible, and reliable tracking of individual whiskers is not possible with the best current software...
master thesis 2018
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Hilmarsson, Saevar (author)
Image processing is found in many fields and in many domains. Advances in<br/>digital image capturing technology allows for faster video rates, of higher quality, than has been seen before and that trend continues. With greater resolution and increased data flow there is also a need for faster and better hardware for image processing. As the...
master thesis 2018
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Chi, Huang-Da (author)
Developing parallel applications to make efficient use of current and emerging parallel architectures remains a big challenge in modern application development where performance is a first-class citizen. Optimizing conventional video filter applications to take advantage of current multi- and many-core architectures is one such application. This...
master thesis 2018
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Gkougkoulias, Konstantinos (author)
In recent years due to the slow down of Moores Law and Dennard Scaling, alternative architectures are starting to be used instead of plain CPU implementations. These new architectures, such as FPGAs and GPUs, offer higher performance to power consumption ratio when compared with a CPU only implementation. But these new approaches have to...
master thesis 2017
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Bakker, Paul (author)
Pavlovian eyeblink conditioning is a powerful experiment used in the field of neuroscience to measure multiple aspects of how we learn in our daily life. To track the movement of the eyelid during an experiment, researchers traditionally made use of potentiometers or electromyography (EMG). More recently, the use of computer vision and image...
master thesis 2017
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Elango, Uttam Kumar (author)
master thesis 2017
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