Now showing items 1-20 of 358

    A double full-stack architecture for multi-core quantum computers 

    Rodrigo Muñoz, Santiago (Date of defense: 2023-12-18)

    (English) Despite its tremendous potential, it is still unclear how quantum computing will scale to satisfy the requirements of its most powerful applications. Continued progress in the fabrication and control of qubits ...

    Job scheduling for disaggregated memory in high performance computing systems 

    Vieira Zacarias, Felippe (Date of defense: 2023-10-09)

    (English) In a typical HPC cluster system, a node is the elemental component unit of this architecture. Memory and compute resources are tightly coupled in each node and the rigid boundaries between nodes limits compute ...

    Acceleration of automatic speech recognition for low-power devices 

    Pinto Rivero, Dennis (Date of defense: 2022-11-09)

    (English) In this thesis, we study the challenges preventing ASR deployment on edge devices and propose innovations to tackle them, hopefully moving the technology a step forward to the future. First, we characterize ...

    Efficient hardware acceleration of deep neural networks via arithmetic complexity reduction 

    Reggiani, Enrico (Date of defense: 2023-10-26)

    (English) Over the past decade, significant progresses in the field of artificial intelligence have led to remarkable advancements in a wide range of technologies. Deep learning, a subfield of machine learning centered ...

    Adapting floating-point precision to accelerate deep neural network training 

    Osorio Ríos, John Haiber (Date of defense: 2023-10-18)

    (English) Deep Neural Networks (DNNs) have become ubiquitous in a wide range of application domains. Despite their success, training DNNs is an expensive task which has motivated the use of reduced numerical precision ...

    Deep learning for spatio-temporal forecasting: benchmarks, methods, and insights from mobility and weather predictions 

    Herruzo Sánchez, Pedro (Date of defense: 2023-10-30)

    (English) This thesis explores the intersection of deep learning and spatio-temporal forecasting, focusing on the challenges and opportunities present in applying machine learning methods to predict complex geospatial and ...

    Advanced hardware prefetching in virtual memory systems 

    Vavouliotis, Georgios (Date of defense: 2023-09-12)

    (English) Despite groundbreaking technological innovations, the disparity between processor and memory speeds (known as Memory Wall) is still a major performance obstacle for modern systems. Hardware prefetching is a ...

    Convergence of high performance computing, big data, and machine learning applications on containerized infrastructures 

    Liu, Peini (Date of defense: 2023-07-17)

    (English) The convergence of High Performance Computing (HPC), Big Data (BD), and Machine Learning (ML) in the computing continuum is being pursued in earnest across the academic and industry. We envision virtualization ...

    Software diagnostics for autonomous safety-critical control-systems based on artificial intelligence 

    Fernández Muñoz, Javier (Date of defense: 2023-07-18)

    (English) Machine Learning (ML) systems allow the efficient implementation of functionalities that can be hard to program by traditional software due to the high spectrum of inputs that hinder the definition of a specific ...

    Scaling deep learning workloads. Applications in computer vision and seismology 

    Cruz de la Cruz, Stalin Leonel (Date of defense: 2023-07-06)

    (English) Deep learning techniques have an enormous impact on the state-of-the-art in many fields, such as computer vision, natural language processing, audio analysis and synthesis, and many others. The increasing computing ...

    Leveraging graph neural networks for optimization and traffic compression in network digital twins 

    Almasan Puscas, Felician Paul (Date of defense: 2023-07-17)

    (English) In recent years, several industry sectors have adapted the Digital Twin (DT) paradigm to improve the performance of physical systems. This paradigm consists of leveraging computational methods to build high-fidelity ...

    Hardware/software solutions to enable the use of high-performance processors in the most stringent safety-critical systems 

    Alcaide Portet, Sergi (Date of defense: 2023-07-19)

    (English) Future Safety-Critical Systems require a boost in guaranteed performance in order to satisfy the increasing performance demands of the state-of-the-art complex software features. Ar1 approach to achieve these ...

    Artificial intelligence solutions for quantum communications 

    Ahmadian, Seyed Morteza (Date of defense: 2023-06-16)

    (English) This Ph.D. thesis focuses on the application of intelligent models to Discrete-Variable Quantum Key Distribution (DV-QKD) protocol. The first objective focuses on providing a method for AI-based polarization ...

    On the data quality improvement of air pollution monitoring low-cost sensor networks using data-driven techniques 

    Ferrer Cid, Pau (Date of defense: 2023-05-08)

    (English) Nowadays, authorities monitor the concentrations of regulated air pollutants in order to assist in decision-making processes, e.g., for the implementation of traffic restrictions, and mitigate the effects of air ...

    Practical strategies to monitor and control contention in shared resources of critical real-time embedded systems 

    Cardona Nadal, Jordi (Date of defense: 2023-04-03)

    (English) In the last decade performance needs in Critical Real-Time Embedded Systems (CRTES) domains like automotive, avionics, railway or space have been steadily on the rise due to the unprecedented computational power ...

    Modelling and predicting extreme behavior in critical real-time systems with advanced statistics 

    Vilardell Moreno, Sergi (Date of defense: 2023-03-13)

    (English) Critical Real-Time Embedded Systems (CRTES) are used in domains like transportation (e.g. avionics, automotive, space, and railway), healthcare, and industrial machinery. This subset of embedded systems requires ...

    Techniques for efficient and secure optical networks 

    Iqbal, Masab (Date of defense: 2023-03-24)

    (English) Optical communication systems are widely adopted and responsible for transporting data traffic from access to metro to core networks supporting society’s information and communication functions. As the traffic ...

    Síntesi d'alt nivell de circuits asíncrons 

    Badia Sala, Rosa Maria (Date of defense: 1994-07-20)

    (Català) A mesura que augmenta el nombre de transistors integrables en un xip, problemes com el desfasament del senyal de rellotge esdevenen cada cop més crítics. Altres avantatges com un consum més baix, una velocitat ...

    Distributed cloud-edge analytics and machine learning for transportation emissions estimation 

    Gutiérrez Torre, Alberto (Date of defense: 2022-11-22)

    (English) In recent years IoT and Smart Cities have become a popular paradigm of computing that is based on network-enabled devices connected providing different functionalities, from sensor measures to domotic actions. ...

    Methodology for malleable applications on distributed memory systems 

    Aguilar Mena, Jimmy (Date of defense: 2022-11-23)

    (English) The dominant programming approach for scientific and industrial computing on clusters is MPI+X. While there are a variety of approaches within the node, denoted by the ``X'', Message Passing interface (MPI) is ...