Departament d'Arquitectura de Computadors

La Universitat Politècnica de Catalunya. Barcelona Tech (UPC) és una institució pública de recerca i d'educació superior en els àmbits de l'enginyeria, l'arquitectura i les ciències.

L’activitat dels seus campus i centres fan de la UPC un punt de referència i, en complicitat amb el teixit productiu, són agent i motor de canvi econòmic i social, en posar en valor la recerca bàsica i aplicada i transferir tecnologia i coneixement a la societat.

Els investigadors i investigadores de la UPC treballen des dels laboratoris i centres de recerca per augmentar la producció científica, valoritzar-la socialment a través de la transferència de resultats i continuar liderant projectes internacionals d’excel·lència, ja sigui a partir d’iniciatives pròpies o en col·laboració amb altres centres de recerca i universitats d’arreu del món.

Futur

Portal de la producció científica dels investigadors de la UPC.

UPCommons

Portal d'accés obert al coneixement de la UPC


Si sou doctor o doctora per la Universitat Politècnica de Catalunya i voleu publicar la vostra tesi a TDX, contacteu amb tdx@upc.edu. Per a més informació consulteu les preguntes més freqüents

Recent Submissions

Improving autonomous driving systems with CPU extensions for point cloud processing 

Exenberger Becker, Pedro Henrique (Date of defense: 2024-10-21)

(English) Autonomous Driving Systems (ADS) are at the cusp of large-scale adoption, promising accident reduction and market potential. However, the complex software and sensor data pressure for better hardware support in ...

Architectural strategies to enhance the latency and energy efficiency of mobile continuous visual localization systems 

Taranco Serna, Raúl (Date of defense: 2024-08-29)

(English) The emergence of new applications such as autonomous machines (e.g., robots or self-driving cars) and XR (Extended Reality) promises to revolutionize how society interacts with technology in the rapidly advancing ...

A highly efficient time-series database approach for monitoring infrastructures 

García Calatrava, Carlos (Date of defense: 2022-12-12)

(English) The rising interest in extracting value from data has led to a broad proliferation of monitoring infrastructures, most notably composed by sensors, intended to collect this new oil. Thus, gathering data has become ...

Optimizing edge cloud deployments for video analytics 

Rivas Barragan, Daniel (Date of defense: 2022-11-09)

(English) As our digital world and physical realities blend together, we, as users, are growing to expect real-time interaction wherever and whenever we want. Newer internet services require lower latency than a data center ...

Hardware knob coordination in multi-threaded systems 

Ortega Carrasco, Cristobal (Date of defense: 2022-11-28)

(English) Every new generation of high performance computing (HPC) processors brings higher complexity to boost performance: the increasing number of cores within the processor itself, cores with the ability to run multiple ...

Towards a domain specific language for computational fluid dynamics in HPC 

Macià Sorrosal, Sandra (Date of defense: 2022-05-26)

(English) High-Performance Computing (HPC) evolves vertiginously. Supercomputers are increasingly powerful and complex machines that require deep expertise to be well-exploited. Currently, scientists develop HPC codes ...

Optimizing serverless architectures for data-intensive analytics workloads 

Nestorov, Anna Maria (Date of defense: 2024-05-03)

(English) Recently, serverless computing has garnered attention from academia and industry due to its on-demand resource provisioning, allowing users to focus solely on their core business logic by breaking down tasks into ...

Advancing the state of the art of directive-based programming for GPUs: runtime and compilation 

Matsumura, Kazuaki (Date of defense: 2024-05-02)

(English) The rapid development in computing technology has paved the way for directive-based programming models towards a principal role in maintaining software portability of performance-critical applications. Efforts ...

A novel approach to web tracking detection and removal with minimal functionality loss 

Castell Uroz, Ismael (Date of defense: 2023-07-06)

(English) echnologies are extensively used to collect huge amounts of personal information from our online activity, including the things we search for, the sites we visit, the people we contact, or the products we buy. ...

Towards resilient wireless networks: mesh backhauls for 5G ultra-dense networks and rural Internet service provision 

Gemmi, Gabriele (Date of defense: 2024-02-22)

(English) This thesis aims to investigate the efficacy and applicability of Wireless Backhaul Network (WBN) in two divergent contexts: ultra-dense urban networks for 5G and connectivity solutions for rural or digitally ...

Multi-agent graph learning-based optimization and its applications to computer networks 

Bernárdez Gil, Guillermo (Date of defense: 2024-03-15)

(English) In the wake of a digital revolution, contemporary society finds itself entrenched in an era where network applications' demands surpass the capabilities of conventional network management solutions. This dissertation ...

Smart and efficient sensor networks operation for 5G and beyond ecosystems 

El Sayed, Ahmad Mohammad (Date of defense: 2024-01-30)

(English) Sensor Networks (SN) will play an integral role in Beyond 5G (B5G) ecosystems, especially for highly-distributed use cases and services such as Digital Twins (DT). Thus, the underlying transport network needs to ...

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 ...

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 ...

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 ...

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 ...

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