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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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van Rijn, Joey (author)Outstanding seizure detection algorithms using electroencephalogram (EEG) recordings have been developed over the past decade. These works mainly focus on best of class performance, which leads to computationally heavy solutions. This limits the applicability of these detection algorithms for hardware implementations such as fieldprogrammable...master thesis 2021
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Koene, Davy (author)With the increase in the amount of data being gathered, the need for data processing is also rising. Furthermore, in addition to the proprietary ISAs that have been prevalent, the free and open RISC-V ISA has seen major interest. The modularity of the RISC-V ISA allows it to be extended with many instruction set extensions. One such extension...master thesis 2021
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Luppes, Bob (author)The increasing volume and latency requirements of big data impose challenges on the processing capacity of existing computing systems. FPGA accelerators can be leveraged to overcome these challenges, but questions remain as to how these accelerators are best deployed to accelerate big data frameworks. This work investigates how future big data...master thesis 2021
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Veselka, David (author)Implantable Medical Devices (IMDs) are deployed in patients to treat a range of medical conditions. Technological advancements have enabled manufacturers to fit IMDs with specialized hardware that accelerates compute-intensive medical therapies next to a software-run host processor. However, mostly hardware acceleration is found in the form of...master thesis 2021
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den Boer, Hans (author)Recently, interest in the use of deep learning technology for RF applications has increased. However, many of these studies are focused on developing deep learning models for a particular RF application. Therefore this master thesis focuses on the implementation of these kinds of deep learning models by using FPGAs such that these deep learning...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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Wouters, Chris (author)A reusable framework for real-time signal processing on airborne SAR was developed for the two main signal processing algorithms used in SAR: range compression and backprojection.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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Dumont, Joep (author)With the increase of available storage bandwidth, CPUs can not keep up with the compute throughput needed to process this amount of incoming data. GPUs and FPGAs are generally better suited for such tasks. To assist FPGAs in their functions, some boards are equipped with one or more high bandwidth memory (HBM) stacks, with a bandwidth of 230 GB...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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Hadnagy, A. (author)Recent trends in large-scale computing demonstrate continuous growth in the need for raw processing performance. At the same time, the slowdown of vertical scaling pushes the industry towards more energy-efficient heterogeneous architectures. With the appearance of FPGAs in the cloud and data centers, a new architecture is offered for offloading...master thesis 2020
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Nonnenmacher, F.M. (author)Through new digital business models, the importance of big data analytics continuously grows. Initially, data analytics clusters were mainly bounded by the throughput of network links and the performance of I/O operations. With current hardware development, this has changed, and often the performance of CPUs and memory access became the new...master thesis 2020
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Aggarwal, S. (author)Big data applications are becoming more commonplace due to an abundance of digital data and increasingly powerful hardware. One of these classes of hardware devices are FPGAs, which are being used today in various ways such as data centers and embedded systems. High performance, power efficiency, and reprogrammability are the primary reasons...master thesis 2020
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Versluis, Niels (author)Elliptic Curve Cryptography (ECC) performance is a major performance bottleneck when serving many VPN clients from a single server on a low-frequency FPGA softcore CPU. Using an area-efficient Elliptic Curve Point (ECP) multiplication accelerator core on the same FGPA, a much higher amount of clients can be served using the same FPGA chip. Using...master thesis 2020
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Optimizing Memory Mapping for Dataflow Inference Accelerators: Efficient Memory Utilization on FPGAsKroes, Mairin (author)Convolutional Neural Network (CNN) inference has gained a significant amount of traction for performing tasks like speech recognition and image classification. To improve the accuracy with which these tasks can be performed, CNNs are typically designed to be deep, encompassing a large number of neural network layers. As a result, the...master thesis 2020
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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