Ofertes de projectes

Consulta ofertes d'altres estudis i especialitats

Gràfics i Realitat Virtual

L'objectiu del projecte és afegir noves mètafores tant de manipulació com d'interació a la plataforma de visualització de models volumètrics en un entorn de realitat virtual.

Gràfics i Realitat Virtual Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Computació d'Altes Prestacions Enginyeria de Serveis Ciència de les Dades

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).

Gràfics i Realitat Virtual Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Computació d'Altes Prestacions Enginyeria de Serveis Ciència de les Dades

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.

Gràfics i Realitat 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

Computació Avançada Ciència de les Dades

This project is a continuation of 2 previous master thesis. In the framework of the Paris 2024 Olympic Games Weather Project, leaded by TriM company, a big amount of data is being collected either on the sea through real time sensors during trainings and racings or from numerical weather prediction models. These data are being stored into a cloud database. Indeed sailing strategy and performance are strongly related with environmental features such as weather conditions, oceanic current and geography.

Xarxes de Computadors i Sistemes Distribuïts Computació d'Altes Prestacions Enginyeria de Serveis Ciència de les Dades

Quantum computing aims to provide significant speedup to many problems by taking advantage of quantum mechanical properties such as superposition and entanglement. Important applications such as Shor's integer factoring algorithm and Grover's unordered database search algorithm provide potentially exponential and quadratic speedups, respectively.

Gràfics i Realitat Virtual Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Enginyeria de Serveis Ciència de les Dades

The main objective of this project is to build a full-stack web app capable of interacting with a Network Digital Twin (NDT) called RouteNet.

Xarxes de Computadors i Sistemes Distribuïts

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Ciència de les Dades

Recent advances in the field of Reinforcement Learning (DRL) are rising a lot of attention due to its potential for automatic control and automatization. Breakthroughs from academia and the industry (e.g, Stanford, DeepMind and OpenAI) are demonstrating that DRL is an effective technique to face complex optimization problems with many dimensions and non-linearities. However, to train a DRL agent in large optimization scenarios still remains a challenge due to the computational intensive operations during backpropagation.

Xarxes de Computadors i Sistemes Distribuïts

Deployment of distributed systems requires an Orchestrator to create pipelines, where a set of heterogeneous functions are connected. The project consists of implementing an Orchestrator and demonstrating the deployment and reconfiguration of pipelines on a 5G network scenario. The Orchestrator will run an optimization algorithm to assign the different functions into datacenters and then coordinate with the Virtual Infrastructure Orchestrator(VIO) and the Software Defined Networking(SDN) controller to create such functions.

Gràfics i Realitat 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

Computació Avançada Computació d'Altes Prestacions

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

Gràfics i Realitat Virtual Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Computació d'Altes Prestacions Enginyeria de Serveis Ciència de les Dades

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.

Xarxes de Computadors i Sistemes Distribuïts

Traditionally, Software Defined Networks (SDN) have been applied for configuring networks for which such configuration was intended to last for hours or even, days. However, the high dynamicity foreseen for 5G scenarios requires adapting SDN to be able to dynamically configure the network with much finer granularity (e.g. in the order of seconds) to adapt to high traffic variations. In this project, we will implement some components for such architecture and test them in an experimental platform.

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada

The objective of this project is to explore federated machine learning in TinyML.

Xarxes de Computadors i Sistemes Distribuïts Ciència de les Dades

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.

Gràfics i Realitat Virtual

The goal of the project is the creation of an exploratory analysis tool for the inspection of gathered data regarding animal and vegetation detections in tropical forests.

Gràfics i Realitat Virtual Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Enginyeria de Serveis Ciència de les Dades

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.

Xarxes de Computadors i Sistemes Distribuïts Ciència de les Dades

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.

Consulta ofertes d'altres estudis i especialitats