Seminars of Innovation and Research in Informatics

Topics include: Introduction on Responsible Research and Innovation Research misconduct Authorship Plagiarism Peer reviews Conflicts of interest Mentor/mentee relationship Collaborative research Presenting the results Intellectual Property Information Privacy.

Monday: 11:00-13:00

This course focuses on modelling two of the highest impact natural hazards, volcanic eruptions and tsunamis. The objective is to give a succinct theoretical overview and then introduce students on the use of different HPC flagship codes included in the Center of Excellence for Exascale in Solid Earth (ChEESE). Learning Outcomes: Participants will learn and gain experience in installing SE codes and related utilities and libraries, running numerical simulations, monitoring the execution of supercomputing jobs, analyzing and visualizing model results. At least University degree in progress on Earth Sciences, Computer Sciences or related area. o Basic knowledge of LINUX o Knowledge of C, FORTRAN, MPI or openMP is recommended o Knowledge of Earth Sciences data formats is recommended (grib, netcdf, hdf,¿) o Basic knowledge of python

Objectives: The objectives of this course are COMPSs is a programming model which is able to exploit the inherent concurrency of sequential applications and execute them in a transparent manner to the application developer in distributed computing platform. This is achieved by annotating part of the codes as tasks, and building at execution a task-dependence graph based on the actual data used consumed/produced by the tasks. The COMPSs runtime is able to schedule the tasks in the computing nodes and take into account facts like data locality and the different nature of the computing nodes in case of heterogeneous platforms. Additionally, recently COMPSs has been enhanced with the possibility of coordinating Web Services as part of the applications. COMPSs supports Java, C/C++ and Python as programming languages. Learning Outcomes: In the course, the COMPSs syntax, programming methodology and an overview of the runtime internals will be given. The attendees will get a first lesson about programming with COMPSs that will enable them to start programming with this framework. A hands-on with simple introductory exercises will be also performed. The students who finish this course will be able to develop simple COMPSs applications and to run them both in a local resource and in a distributed platform (initially in a private cloud Prerequisites: Programming skills in Java

Objectives: The objective of this course is to give an overview of BSC storage solutions, Hecuba and dataClay. These two platforms allow to easily store and manipulate distributed data from object-oriented applications, enabling programmers to handle object persistence using the same classes they use in their programs, thus avoiding time consuming transformations between persistent and non-persistent data models. Also, Hecuba and dataClay enable programmers to transparently manage distributed data, without worrying about its location. This is achieved by adding a minimal set of annotations in the classes. Learning Outcomes In the course, the Hecuba and dataClay syntax, programming methodology and an overview of their internals will be given. Also, an overview of COMPSs at user level will be provided in order to take advantage of the distribution of data with both platforms. The attendees will get a first lesson about programming with the common storage interface that will enable them to start programming with both frameworks. A hands-on with simple introductory exercises will be also performed for each platform, with and without COMPSs to distribute the computation. The students who finish this course will be able to develop simple Hecuba and dataClay applications and to run them both in a local resource and in a distributed platform (initially in a private cloud)

The objective of this PATC course is to cover the basics of a high performance computing (HPC) environment oriented towards earth science applications, specifically chemical weather modelling and climate modelling. More precisely, the course will cover: - Introduction to earth science fundamentals and modelling; - Basic usage of an HPC environment: shell, compilers, libraries, file systems, queuing system; - Build and configure targeted earth science applications with the NMMB/BSC-CTM chemical transport model and with the EC-EARTH climate model; - Execute and monitor numerical experiments using a workflow manager; - Analyse and visualise model outputs with a wide set of tools. Prerequisites: - At least University degree in progress on Earth Sciences, Computer Sciences or related area - Basic knowledge of UNIX - Knowledge of C, FORTRAN, MPI or openMP is recommended - Knowledge of Earth Sciences data formats is recommended (grib, netcdf, hdf,¿) - knowledge of R and python

The objectives of this course are to understand the fundamental concepts supporting message-passing and shared memory programming models. The course covers the two widely used programming models: MPI for the distributed-memory environments and OpenMP for the shared-memory architectures. The course also presents the main tools developed at BSC to get information and analyze the execution of parallel applications, Paraver and Extrae. It also presents the Parallware Assistant tool, which is able to automatically parallelize a large number of program structures, and provide hints to the programmer with respect to how to change the code to improve parallelization. It deals with debugging alternatives, including the use of GDB and Totalview. The use of OpenMP in conjunction with MPI to better exploit the shared-memory capabilities of current compute nodes in clustered architectures is also considered. Paraver will be used along the course as the tool to understand the behavior and performance of parallelized codes. The course is taught using formal lectures and practical/programming sessions to reinforce the key concepts and set up the compilation/execution environment.

HackUPC is the first student hackathon in Spain. This will be our sixth edition with 700 awesome hackers and lots of side activities to learn new technologies, meet interesting people and have fun. Come make history with us!

Friday 3pm to Sunday 5pm

Conferencia de Python en la que se imparten varias charlas y talleres sobre Machine Learning y Big Data con Python. La agenda de la conferencia, en la que pueden encontrarse todas las charlas/talleres anteriormente mecionados puede encontrarse en la web de la PyCon (adjuntada en la petición).

GECON 2019 builds upon the very successful tradition of the conference previous editions since 2003, (http://www.gecon-conference.org). GECON solicits contributions that are interdisciplinary, combining business and economic aspects with engineering and computer science related themes. Contributions to this conference can include extensions to existing technologies, successful deployments of technologies, economic analyses, analyses of technology adoptions, and theoretical models. We welcome papers that combine micro- and macro-economic principles with resource management strategies in computer science and engineering. Case studies, which demonstrate practical use of economic strategies, benefits and limitations, are particularly encouraged. The purpose of this event is to gather original work and build a strong multidisciplinary community in this increasingly important area of a future information and knowledge economy.

http://gecon2019.gecon.info/index.php/program

GECON 2019 builds upon the very successful tradition of the conference previous editions since 2003, (http://www.gecon-conference.org). GECON solicits contributions that are interdisciplinary, combining business and economic aspects with engineering and computer science related themes. Contributions to this conference can include extensions to existing technologies, successful deployments of technologies, economic analyses, analyses of technology adoptions, and theoretical models. We welcome papers that combine micro- and macro-economic principles with resource management strategies in computer science and engineering. Case studies, which demonstrate practical use of economic strategies, benefits and limitations, are particularly encouraged. The purpose of this event is to gather original work and build a strong multidisciplinary community in this increasingly important area of a future information and knowledge economy.

http://gecon2019.gecon.info/index.php/program

GECON 2019 builds upon the very successful tradition of the conference previous editions since 2003, (http://www.gecon-conference.org). GECON solicits contributions that are interdisciplinary, combining business and economic aspects with engineering and computer science related themes. Contributions to this conference can include extensions to existing technologies, successful deployments of technologies, economic analyses, analyses of technology adoptions, and theoretical models. We welcome papers that combine micro- and macro-economic principles with resource management strategies in computer science and engineering. Case studies, which demonstrate practical use of economic strategies, benefits and limitations, are particularly encouraged. The purpose of this event is to gather original work and build a strong multidisciplinary community in this increasingly important area of a future information and knowledge economy.

http://gecon2019.gecon.info/index.php/program

This course aims to provide an extremely practical vision of the application to real problems of modeling techniques, from the most basic to the most state-of-the art ones, in highly quantitative business environments (banking and finance). The goals of this course is to learn the challenges involved in creating a model in the real world from obtaining the data to the best model to be used and the validation mechanisms depending on the type of problem. Good practices and description of the usual problems in a large modeling project.

The course taught by Dr. Christian Weiss comprises an introduction to the modeling of discrete time-series, by looking at the different models for discrete count-like, ordinal and categorical time-series. Throughout the lectures, models and methods are illustrated with diverse real-data time series using the statistical software R.

25-27 9:00~13:00, 28 8:00~11:00

Knowing how to classify a categorical response variable based on information provided by predictor variables is a necessary skill for any data scientist. This course will teach statistical and machine learning methods for classification and illustrate their application by analyzing a variety of real datasets using R. The participants will be given a similar dataset to analyze to gain hands-on experience.Course goalsThis course will provide a hands-on training in statistical and machine learning methods for classification, their implementation using R, and their application.Course contents The course will be taught using the book, An Introduction to Statistical Learning with Applications in R, by James, Witten, Hastie, and Tibshirani, Springer, 2013. A free PDF copy of the book can be downloaded from http://www-bcf.usc.edu/~gareth/ISL/. The following is a tentative schedule and list of topics to be covered: