Ofertas de proyectos

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Gráficos y Realidad Virtual Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones Ingeniería de Servicios Ciencia de los Datos

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).

Gráficos y Realidad Virtual Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones Ingeniería de Servicios Ciencia de los Datos

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.

Ingeniería de Servicios Ciencia de los Datos

Traditional Machine Learning systems require lots of training data to learn a particular task, and they are usually resilient to some noise in the data. But Large Language Models (LLM) such as GPT-3 or BLOOM are already trained in zillions of data, and much less data are needed to fine-tune them for a specific task. However, these data must be highly consistent and noise-free to ensure proper learning of the task. The project consist of devising and implentig a tool able to assists data curators in the creation, maintenance, and consistency checking of these datasets.

Gráficos y Realidad Virtual

Navigation meshes are necessary to represent the walkable space of an environment so that agents can perform pathfinding and move through them. Current navigation meshes tend to flatten the environmetn to represent it as 2D polygons connected by edges (square cells, triangles or larger convex polygons). This abstraction presents problems when dealing with complex outdor geometry where the terrain may not be completely flat. With this project, we would develop a novel navigation mesh that can keep the complexity of any 3D input geometry, while still generating small graphs

Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones

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

Gráficos y Realidad Virtual

Dimensionality reduction algorithms transform high-dimensional data to lower dimensions, usually 2D or 3D. Analyzing the results of such algorithms typically is carried out using 2D plots and measures. The goal of the project is the creation of an application that facilitates the visual comparison and exploration of those spaces.

Computación Avanzada Computación de Altas Prestaciones

The key objective of this work is the integration of DMPlex functionalities with PETGEM.

Gráficos y Realidad Virtual Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones Ingeniería de Servicios Ciencia de los Datos

The Barcelona Neural Networking Center (BNN-UPC) is offering two positions to develop the Master Thesis in the field of Graph Neural Networks (GNN) applied to computer networking. This TFM will be fully funded and will be carried in the context of a large industrial project with a major multinational technology company.

Gráficos y Realidad Virtual

Reading charts in desktop and virtual reality environments can be difficult depending on the configuration of different parameters such as the width and height of different visual marks. The project aims to explore the perceptual limits of a set of well-known visualization techniques in desktop and VR-based environments.

Redes de Computadores y Sistemas Distribuidos Ciencia de los Datos

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

Computación de Altas Prestaciones

Programming models for HPC have to be adapted to a new paradigm where every HPC system has accelerators. In BSC we develop the OmpSs-2 shared-memory programming model, which has support for offloading tasks to GPUs and FPGAs. However, programmers must still manage memory copy operations manually, or use unified memory. The project will consist on implementing automatic memory management inside the OmpSs-2 runtime, tracking and moving data transparently from hosts to accelerators and vice-versa.

Gráficos y Realidad Virtual

This master's thesis aims to analyze the feasibility of a remote VR system based on the use of mobile devices with cardboard glasses and low-cost interaction devices. It will start from a system based on HTC-VIVES programmed with Unity. Different portability alternatives to the new platform will be analyzed both in terms of the rendering of the models (locally or on a server) and the limitations of the interaction and connection between students and teacher. A prototype will be developed with basic interaction techniques and its usability will be analyzed.

Gráficos y Realidad Virtual Redes de Computadores y Sistemas Distribuidos Computación Avanzada Ingeniería de Servicios Ciencia de los Datos

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.

Redes de Computadores y Sistemas Distribuidos Ciencia de los Datos

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.

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