Departament d'Arquitectura de Computadors: Recent submissions
Now showing items 21-40 of 373
Deep learning for spatio-temporal forecasting: benchmarks, methods, and insights from mobility and weather predictions
(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
(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
(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
(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
(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 ...
Hardware/software solutions to enable the use of high-performance processors in the most stringent safety-critical systems
(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 ...
Leveraging graph neural networks for optimization and traffic compression in network digital twins
(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 ...
Artificial intelligence solutions for quantum communications
(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
(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
(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
(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
(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
(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
(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
(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 ...
Leveraging disaggregated accelerators and non-volatile memories to improve the efficiency of modern datacenters
(English) Traditional data centers consist of computing nodes that possess all the resources physically attached. When there was the need to deal with more significant demands, the solution has been to either add more nodes ...
Exploiting optical signal analysis for autonomous communications
(English) Optical communications have been extensively investigated and enhanced in the last decades. Nowadays, they are responsible to transport all the data traffic generated around the world, from access to the core ...
Enhanced clustering analysis pipeline for performance analysis of parallel applications
Clustering analysis is widely used to stratify data in the same cluster when they are similar according to the specific metrics. We can use the cluster analysis to group the CPU burst of a parallel application, and the ...
Real-time high-performance computing for embedded control systems
The real-time control systems industry is moving towards the consolidation of multiple computing systems into fewer and more powerful ones, aiming for a reduction in size, weight, and power. The increasing demand for higher ...
Resilience for large ensemble computations
With the increasing power of supercomputers, ever more detailed models of physical systems can be simulated, and ever larger problem sizes can be considered for any kind of numerical system. During the last twenty years ...
