Courses 2018/2019

1st Semester


2nd Semester



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Past courses

2017/2018


2013/2014


2012/2013


2011/2012


2010/2011



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Ph.D. students advised



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Master theses / Final Projects

Advised

  • "Accelerated Simulation of Population Dynamics P Systems with GPU", by Andrés Doncel Ramírez. Co-advised with Daniel H. Campora-Pérez. July 2018.
  • "A Study of a Parallel Implementation for the Pixel VELO Subdetector", by Daniel H. Campora Pérez. Co-advised with Fernando Sancho-Caparrini and Niko Neufeld, in collaboration with CERN. September 2013. Extraordinary Award of Master Thesis Universidad de Sevilla.
  • "Simulation of probabilistic P systems on GPUs", by Adolfo Gastalver-Rubio. Co-advised with Ignacio Pérez-Hurtado. September 2012.
  • "Acceleration of membrane system simulations on solutions to SAT using GPUs", by Jesús Pérez-Carrasco. July 2012. Distinction.
  • "Web analyzer of P-Lingua", by José González Pareja. Co-advised with Ignacio Pérez-Hurtado. July 2012.
  • "A generic compiler for P-Lingua", by Francisco González Cordero. Co-advised with Ignacio Pérez-Hurtado. September 2011.
  • "Multi-agent systems on CUDA", by Daniel H. Campora Pérez. Co-advised with Fernando Sancho-Caparrini. July 2010. Distinction.

Proposals

Find next a list of proposed master thesis topics. If you feel interested in one of them, or something similar, just get in touch with you.

1. Accelerated Simulation of PDP systems from pLinguaCore
- Description:
The PDP systems form a formal computational modeling framework for population dynamics that has been successfully employed with real ecosystems, such as the Bearded Vulture in the Catalan Pyrenees and the Zebra Mussel in the Ribarroja Reservoir. Experts in these ecosystems conduct virtual experiments using the MeCoSim tool, which in turn makes use of pLinguaCore as a simulation engine for PDP systems. However, this simulator is inefficient for certain models and ecosystems, so another PDP system simulator was developed that makes use of massively parallel devices such as graphics cards, called ABCD-GPU. CUDA technology is used for this purpose, which leverages the thousands of cores found in today's GPUs and has been adopted worldwide for supercomputing. The ABCD-GPU simulator is a tool that is still in beta phase and not connected to P-Lingua (and therefore not MeCoSim). The aim of this master thesis is to implement improvements in the simulator and the development of an extension of the P-Lingua simulation framework so that it can be connected to ABCD-GPU in the tasks that require this potential.
- Requirements:
Theoretical knowledge of Membrane Computing. Knowledge of Java and C/C++, and basic knowledge of parallel programming.

2. Analysis and design of membrane systems for its simulation on GPUs
- Description: Membrane cell systems are bioinspired devices that have applications at both theoretical (theory of computability) and practical level (modelling of biological systems, ecosystems, etc.). Simulation of these systems is a very active research topic, and the first software applications available are relatively inefficient. It is therefore necessary to accelerate simulators using parallel technology. GPU computing opens up a whole new range of possibilities with CUDA and OpenCL technologies. However, some current GPU-based simulators do not achieve a noticeable improvement in efficiency. A new avenue is to study which models fit best with the GPU architecture. This master thesis aims to develop a CUDA simulator for various P-system models (e. g., Kernel P systems) and analyze those ingredients that are properly simulated on the GPU.
- Requirements: Theoretical knowledge of Membrane Computing. Basic knowledge of parallel programming and C/C++ or Python language.

3.
Semantic analysis of videos through Deep Learning
- Description: Thousands of movies are produced each year, and therefore automatic understanding of content is important for developing film recommendation systems, efficient storage, censorship assistance, scene extraction systems, etc. This is why we have begun to develop Deep Learning-based algorithms for automatic extraction of video tags, intelligent segmentation of scenes, and automatic categorization of scenes and beat events. The aim of this master thesis is to extend these algorithms, providing improvements in the convolutional networks used through transfer learning, expanding the categories and types of studio films, and/or processing other types of multimedia in addition to frames, such as audio and text.
- Requirements: Theoretical knowledge of Machine Learning and Neural Networks. Python language

4.
Accelerated simulation of bio-inspired systems with OpenCL
- Description: Membrane cell systems are bioinspired devices that have applications at both theoretical (theory of computability, complexity, etc.) and practical level (modelling of biological systems, ecosystems, etc.). The simulation of these systems is still under development, and the first software applications available are relatively inefficient. It is therefore necessary to accelerate simulators using parallel technology. GPU computing opens up a whole new range of possibilities with CUDA and OpenCL technologies. The first GPU-based simulators were developed on CUDA, a technology specific to NVIDIA. Therefore, in this master thesis, the aim is to study these simulators and analyze a new development using OpenCL technology, which offers a standard platform that serves both GPU technology of AMD, Intel multiprocessors, FPGAs, etc. 
- Requirements: Theoretical knowledge of Membrane Computing. Basic knowledge of parallel programming and C/C++ language.

5.
Development of intelligent and parallel algorithms for the LHC
- Description: This project is part of a collaboration with CERN to develop intelligent algorithms and its parallel implementation in CUDA for processing data generated in the LHCb particle detector.

6. Optimized simulation of cellular systems in Nvidia/CUDA 
- Description: The new generation of GPUs (graphics processors) offer great computing power at lower cost and energy consumption. General-purpose computing techniques (GPGPU) and programming languages such as CUDA and OpenCL are used for this purpose. The use of these massively parallel processors opens up new avenues for the efficient simulation of cellular systems. This master thesis aims to improve the performance of a P system simulator with active membranes written in CUDA, using techniques such as sparse matrix or tailing, and optimizing the code with the improved architecture of the new NVIDIA Turing cards.
- Requirements: Basic knowledge of parallel programming and C/C++ language


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NVIDIA DLI University Ambassador


I am a University Ambassador of NVIDIA Deep Learning Institute (DLI). Moreover, I am a certified DLI instructor for the following courses:
  • Fundamentals of Deep Learning for Computer Vision (October 2018)
  • Fundamentals of Accelerated Computing with CUDA C/C++ (pending).

Moreover, I have been a Teaching Assistant at the following training sessions:
  • Deep Learning for Healthcare Image Analysis, MICCAI, September 2018, Granada, Spain
  • Fundamentals of Deep Learning for Computer Vision, GTC Europe, October 2018, Munich, Germany.


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Other teaching activities


  • Assistant Teacher briefly collaborating on the project Artificial Intelligence... ¡Naturally! of the Summer Science Campus (for outstanding high school students), teaching an introduction to AI and Deep Learning. Organized by the Spanish government and FECYT (Seville, July 2018).
  • Assistant Teacher in the project Artificial Life... ¿Intelligent? of the Summer Science Campus (for outstanding high school students), teaching an introduction to GPU computing. Organized by the Spanish government and FECYT (Seville, July 2013 and July 2014).
  • Assistant Teacher in the project Intelligent Computing with Living Organisms of the Summer Science Campus (for outstanding high school students), teaching an introduction to GPU computing. Organized by the Spanish government and FECYT (Seville, July 2011 and July 2012).
  • Invited speaker:
    • Course Bioinspired Computing, of the Master in Logic, Computing and Artificial Intelligence, University of Seville (year 2013).
    • Course Teaching Innovation and Introduction to Educational Research,speciality in informatics, of the Master in Secondary Education andProfessional Formation, University of Seville (years 2013-2014, 2012-13, 2011-12 and 2010-11). Proposal of research projects about teaching GPU computing and CUDA in high schools.
    • Course Computational Simulation and Analysis in Systems Biology, of the Master in Logic, Computing and Artificial Intelligence, University of Seville (years 2011, 2012, 2013, 2014).
    • Course Nature, a source of computational inspiration, organized by Institute of Educational Sciences of the University of Lleida (year 2010).


Spanish

Office hours (2018/19)

Tuesdays 15:30 - 18:30
Wednesdays 09:00 - 12:00

Contact me by email first, especially if you cannot come in any of these slots.


Fellowships and Internships at Fraunhofer IIS

If you are interested on working at Fraunhofer IIS (Germany), there are several options. Get in touch with me for orientation:

- For undergraduate students: Internships or Student Assistants jobs at the Moving Picture Technologies Department (seek for CUDA/OpenCL related offers).

- For postdocs: ERCIM fellowships, with application rounds on April and September. Contact us before applying.