Supercomputing & Research

• Sessió 1. Programming Models. 1 de febrero, 8h00 - 11h00

De 8h00 a 9h30 Programming Models

Xavier Martorell

This session will introduce the group of Programming Models @BSC, including the main lines of research on simplifying the programming of current and future heterogenous architectures. We will show the development of the OmpSs programming model, and how we support SMP multicore machines, GPUs, and FPGAs.

Agenda:

• Programming Models group @ BSC (15')
• The OmpSs Programming Model (45')
• Hands-on demo on various applications and environments (30')

De 9h30 a 11h00 Supercomputación en investigación biomédica: sistema cardiovascular

Mariano Vázquez

En la charla se mostrarán ejemplos de aplicación de la supercomputación en simulaciones a nivel órgano del sistema cardiovascular. Las simulaciones están basadas en el código Alya, desarrollado en el BSC. Se mostrarán simulaciones sobre el corazón y su función, de despliegue de stents en arterias o de uso de biochips computacionales en industria farmacéutica.

• Sessió 2 Earth Science Department BSC. 2 de febrero, 11h00 - 14h00

D'11h00 a 14h00  Earth Science Department BSC

Kim Serradell

A series of talks will introduce the research done in the Earth Sciences Department of the Barcelona Supercomputing Center on Climate Prediction, Atmospheric Composition and Computational Earth Sciences as well as the Earth System Services derived from the activities of the Department.

The Department develops and applies state-of-the-art Earth Systems Models to study the evolution of the climate, the atmospheric composition and their interrelations.

Agenda:

• Climate prediction/ES Services (45 mins)
• Atmospheric Composition/ES Services (45 mins)
• Break (15 mins)
• Computational Earth Sciences (45 mins)
• Discussion (30 mins)

• Sessió 3 Big Data and Machine Learning applied to Science and Engineering. 2 de febrero, 15h00 - 18h00

De 15h00 a 16h30 Big Data and Machine Learning applied to Science and Engineering

Carlos Carrasco Jiménez

Machine learning (ML) algorithms have been around for a long time, but the ability to apply those algorithms to large volumes of data with a variety of data types being generated at high velocity is a recent development, a concept known as Big Data. Advances in computing capabilities such as storage and processing power have led companies in the private sector to solve problems and identify business opportunities exploiting large amounts of historical data and more recently streams of real time data using ML and Big Data technologies. Furthermore, different fields in science and engineering are turning towards ML and Big Data infrastructures in order to improve our understanding of the world and discover new insights that pose a challenge with traditional methodologies and technologies. This lecture will introduce the concepts of Big Data, Machine Learning and their application to science and engineering.

De 16h30 a 18h00 Urban scale video and data analysis, simulation, and visualization of crowds

Isaac Rudomin, Leonel Toledo, Ivan Rivalcoba

We will discuss our work in urban-scale crowd video and data analysis, simulation, and visualization, as well as their acceleration using heterogeneous clusters with GPUs. Our main contributions are the development of new behavior models that conform to real data, the ability to scale the system by adding computing resources as needed without making programming modifications and the combination of analysis, simulation, and visualization techniques that help us achieve large-scale crowd simulations with realistic behavior.