Searched for: mods_note_programme_s%3A%22Computer%255C%2BEngineering%22
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Sudhakar, Varun (author)
The ever-increasing energy demands of traditional computing platforms (CPU, GPU) for large-scale deployment of Artificial Intelligence (AI) has spawned an exploration for better alternatives to existing von-Neumann compute architectures. Computation In-Memory (CIM) using emerging memory technologies such as Resistive Random Access Memory (RRAM)...
master thesis 2022
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Buis, Jan Maarten (author)
Renewed interest in memory technologies such as memristors and ferroelectric devices can provide opportunities for traditional and non-traditional computing systems alike. To make versatile, reprogrammable AI hardware possible, neuromorphic systems are in need of a low-power, non-volatile and analog memory solution to store the weights of the...
master thesis 2022
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Zaharieva, Nikoleta (author)
Natural disasters can significantly disturb communication networks. There are examples of events causing massive connectivity failures in the past, such as the Great East Japan Earthquake. Network protection mechanisms have been developed to cope with the destructive power of natural disasters and mitigate their impact on connections...
master thesis 2022
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Rudge, Zacharia (author)
With recent breakthroughs in AI and deep learning, applying these techniques to on-board computers for space applications has grown in interest to engineers on space applications. The space field brings its own challenges, such as reliability and power restrictions. The proposed solution in this work concerns a neuromorphic accelerator for a...
master thesis 2021
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Molenkamp, Michaël (author)
Many devices currently connect to the internet. Some are pretty well secured, while others lack security due to bugs or other vulnerabilities. A scanner searches for available services on the internet or computer host using standard network protocols. An adversary uses a scanner to search for leaks in security. However, scanners encode their...
master thesis 2021
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Verrer, Daan (author)
Modern implementations of encryption algorithms on CPU’s that use frequent memory lookups of precomputed functions, are vulnerable to Cache based Side­Channel Attacks. The ρ­-VEX processor, a runtime reconfigurable VLIW processor developed at the Computer and Quantum Engineering department at the TU Delft was identified to possibly allow for...
master thesis 2021
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Busa, Barnabás (author)
This thesis evaluates standard statistical and machine learning models for early fault detection for Valve Regulated Lead-Acid (VRLA) batteries in uninterruptible power supply (UPS) units. Unexpected battery failures in emergency support systems throughout CERN can endanger working personnel. Thus the minimization of downtime of such battery...
master thesis 2021
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Mrahorović, Mirza (author)
Deep Neural Network (DNNs) have increased significantly in size over the past decade. Partly due to this, the accuracy of DNNs in image classification and speech recognition tasks has increased as well. This enables a great potential for such models to be applied in real-world applications. However, due to their size, the compute and power...
master thesis 2021
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Yönsel, Yüksel (author)
There has been an increasing interest in moving computation closer to storage in recent years due to significant improvements in memory technology. FPGAs were proven to be an exciting candidate for accelerating database workloads since they provide an energy-efficient, reconfigurable and high-performance computation platform. Therefore, FPGAs...
master thesis 2021
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Arriëns, Roy (author)
A big catalyst of the AI revolution has been Artificial Neural Networks (ANN), abstract computation models based on the biological neural networks in the brain. However, they require an immense amount of computational resources and power to configure and when deployed often are dependent on cloud resources to function. This makes ANNs less...
master thesis 2021
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van Leenen, Ryan (author)
Some server hosters facilitate cyber crime either intentionally (so called “bulletproof hosters”) or unintentionally (“bad hosters”). When dealing with uncooperative hosters during forensic investigations, it may sometimes be necessary to collect data or information on the servers without help from the owner of the server....
master thesis 2021
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Saxena, Mudit (author)
As of 2021, the world economic forum deems cyber-security failures as one of the most potent threats to the world. According to a McAfee report, the cost of cybercrimes in 2020 reached nearly 1 trillion US dollars, which was around 50 percent more than what it was in 2018. Exacerbating the already mammoth financial implication of such a failure...
master thesis 2021
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Zografou, Artemis (author)
Computation-In-Memory (CIM) employing Resistive-RAM<br/>(RRAM)-based crossbar arrays is a promising solution to implement Neural Networks (NNs) on hardware, such that they are efficient with respect to consumption of energy, memory, computational resources, and computation time. In this respect, Binary NNs (BNNs), where the weights obtain single...
master thesis 2021
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Smaran Adarsh, SMARAN ADARSH (author)
Quantum computing is an emerging technology that combines the principles of both computer science and quantum mechanics to solve computationally challenging problems significantly faster than the current classical computers. In this thesis, a proof of concept to generate hardware-executable quantum circuits for Noisy Intermediate-Scale Quantum ...
master thesis 2021
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Vermaat, Bas (author)
The ρ-VEX is a processor designed at the Computer Engineering lab at TU Delft to be reconfigurable at runtime, resulting in a processor that can combine or separate instruction lanes according to the program requirements. The current cache for the ρ-VEX processor is direct mapped and always identical to the instruction group configuration. This...
master thesis 2021
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de Rooij, Martijn (author)
Low latency Convolutional Neural Network (CNN) inference research is gaining more and more momentum for tasks such as speech and image classications. This is because CNNs have the ability to surpass human accuracy in classication of images. For improving the measurement setup of gravitational waves, low latency CNNs inference are researched. The...
master thesis 2021
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Engelen, Max (author)
Complex mathematical models are used in computational neuroscience to stimulate brain activity to understand the biological processes involved. The simulation of such models is computationally costly, and thus highperformance<br/>computing systems are selected as a potential solution to increase performance.<br/>This thesis aims to implement a...
master thesis 2021
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Kerkhof, Jorden (author)
The urgency for high-security products for industrial networks is increasing as malicious hackers are improving their accessibility tools. A common practice for a company to protect its sensitive data is network segmentation. The network is segmented in different domains with distinctive security levels. The sensitive data is stored and managed...
master thesis 2021
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Nicou, Nikolas (author)
The field of Computing has been a significant catalyst for innovation across various segments of our lives. Computational neuroscience keeps demanding increased perfor- mance to implement powerful simulators able to closely approximate brain behavior using complex mathematical models. This resulted in various High-Performance Com- puting systems...
master thesis 2020
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Mattei, Vieri (author)
Modified Newtonian Dynamics (MOND) can account for a variety of phenomena on galactic scales without the need for dark matter, but it cannot fully explain the mass contained in galaxy clusters. We explore two possible solutions to this problem: relativistic extensions of MOND, and FEM simulations of the apparent matter distribution in clusters,...
master thesis 2020
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