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Enginyeria de Computadors Computació Sistemes d'informació Tecnologies de la informació

Companies and scientists working in areas such as finance or genomics are generating enormously large datasets (in the order of petabytes) commonly referred as Big Data. How to efficiently and effectively process such large amounts of data is an open research problem. Since communication is involved in Big Data processing at many levels, at the NaNoNetworking Center in Catalunya (N3Cat) we are currently investigating the potential role of wireless communications in the Big Data scenario. The main focus of the project is to evaluate the impact of applying wireless communications and networking methods to processors and data centers oriented to the management of Big Data. OBJECTIVES =========== N3Cat is looking for students wanting to work in the area of wireless communications for Big Data. To this end, the candidate will work on one of the following areas: - Traffic analysis of Big Data frameworks and applications, as well as in smaller manycore systems. - Channel characterization in Big Data environments: indoor, within the racks of a data center, within the package of CPU, within a chip. - Design of wireless communication protocols for computing systems from the processor level to the data center level.

Enginyeria de Computadors Computació

Machine Learning (ML) has taken the world by storm and has become a fundamental pillar of engineering. As a result, the last decade has witnessed an explosive growth in the use of deep neural networks (DNNs) in pursuit of exploiting the advantages of ML in virtually every aspect of our lives: computer vision, natural language processing, medicine or economics are just a few examples. However, NOT all DNNs fit to all problems: convolutional NNs are good for computer vision, recurrent NNs are good for temporal analysis, and so on. In this context, the main focus of N3Cat and BNN-UPC is to explore the possibilities of the new and less explored variant called Graph Neural Networks (GNNs), whose aim is to learn and model graph-structured data. This has huge implications in fields such as quantum chemistry, computer networks, or social networks among others. OBJECTIVES =========== N3Cat and BNN-UPC are looking for students wanting to work in the area of Graph Neural Networks studying their uses, processing architectures, and algorithms. To this end, the candidate will work on ONE of the following areas: - Investigating the state of the art on this area, surveying the different works done in terms of applications, processing frameworks, algorithms, benchmarks, datasets. This can be taken from a hardware or software perspective. - Helping to build a testbed formed by a cluster of GPUs that will be running pyTorch or Tensorflow. We will instrument the testbed to measure the computation workload and communication flows between GPUs. - Analyzing the communication workload of running a GNN either in the testbed or by means of architectural simulations. - Developing means of accelerating GNN processing in software (e.g., improving scheduling of the message passing) or hardware (e.g. designing a domain-specific architecture).

Enginyeria de Computadors Computació Tecnologies de la informació

Quantum computers promise exponential improvements over conventional ones due to the extraordinary properties of qubits. However, a quantum computer faces many challenges relative to the movement of qubits which is completely different than the movement of classical data. This thesis delves into these challenges and proposes solutions to create scalable quantum computers


The world economy is organized in complex multilayer networks of interactions, in which countries are connected with each other through different interactions, such as trade and financial investment. This networked substrate is the ultimate responsible for the propagation of economic shocks, such financial crisis or economic isolation due to the imposition of sanctions or trade tariffs. In this work, we will analyze the multiplex network reconstructed using yearly data of bilateral trade and financial positions between countries, available at the IMF.


The scope of this TFG project is to address the second part of the 16th Hilbert problem numerically and develop a parallel code that will run on a dedicated NVidia Titan V graphic card (15 TFLOPS float performance). The parallel code is to be written either directly in CUDA programming language either by using python or Julia frontends. There is a dedicated computer with two NVidia graphic cards that can be used for running the code.


Desenvolupament d'una aplicació en un entorn de RV immersiu (casc RV) dins la qual el participant ha de poder realitzar un dels processos establerts en el protocol de donació i trasplantament d'òrgans. La idea general és construir un entorn virtual creïble que permeti la pressa de decisions de l'usuari i actuï en conseqüència. L'aplicació ha de permetre enregistrar totes les decisions i/o accions realitzades per tal de poder avaluar l'actuació de l'usuari en el procés. A més, l'entorn virtual haurà de ser dinàmic permetent provocar accions d'emergència.

Enginyeria de Computadors Computació Sistemes d'informació Enginyeria del Software Tecnologies de la informació

Optimize parallel numerical applications for climate modelling to efficiently exploit large multi-core clusters

Computació Tecnologies de la informació

UPC and Nestlé are offering a new position to develop the TFG in the field of Machine Learning and Cybersecurity. This TFG will be fully funded (internship) and carried out in collaboration with the Global Security Operations Center of Nestlé and UPC.

Computació Sistemes d'informació Enginyeria del Software Tecnologies de la informació

Web tracking technologies are extensively used to collect large amounts of personal information (PI), including the things we search, the sites we visit, the people we contact, or the products we buy. Although it is commonly believed that this data is mainly used for targeted advertising, some recent works revealed that it is exploited for many other purposes, such price discrimination, financial credibility, insurance coverage, government surveillance, background scanning or identity theft. The main objective of this project is to apply network traffic monitoring and analysis technologies to uncover the particular methods used to track Internet users and collect PI. This project will be useful for both Internet users and the research community, and will produce open source tools, real data sets, and publications revealing most privacy attempting practices. Some preliminary results of our work in this area were recently published in Proceedings of the IEEE (IF: 9.237) and featured in a Wall Street Journal article.

Computació Sistemes d'informació Enginyeria del Software Tecnologies de la informació

Most EU citizens are concerned about online privacy. EPRIVO aims at building a European data-driven observatory that automatically looks for online services that do not respect our privacy rights.

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