DEEP: Hybrid Approach for Deep Learning

Trabajo presentado al ISC High Performance, celebrado en Frankfurt (Alemania) del 16 al 20 de junio de 2019.The DEEP-HybridDataCloud project researches on intensive computing techniques such as deep learning, that require specialized GPU hardware to explore very large datasets, through a hybrid-cloud approach that enables the access to such resources. DEEP is built on User-centric policy, i.e. we understand the needs of our user communities and help them to combine their services in a way that encapsulates technical details the end user does not have to deal with. DEEP takes care to support users of different levels of experience by providing different integration paths. We show our current solutions to the problem, which among others include the Open Catalog for deep learning applications, DEEP-as-a-Service API for providing web access to machine learning models, CI/CD pipeline for user applications, Testbed resources. We also present our use-cases tackling various problems by means of deep learning and serving to demonstrate usefulness and scalability of our approach.DEEP HybridDataCloud receives funding from the European Union's Horizon 2020 research and innovation programme under agreement RIA 777435

BIGSEA: A Big Data analytics platform for public transportation information

Analysis of public transportation data in large cities is a challenging problem. Managing data ingestion, data storage, data quality enhancement, modelling and analysis requires intensive computing and a non-trivial amount of resources. In EUBra-BIGSEA (Europe–Brazil Collaboration of Big Data Scientific Research Through Cloud-Centric Applications) we address such problems in a comprehensive and integrated way. EUBra-BIGSEA provides a platform for building up data analytic workflows on top of elastic cloud services without requiring skills related to either programming or cloud services. The approach combines cloud orchestration, Quality of Service and automatic parallelisation on a platform that includes a toolbox for implementing privacy guarantees and data quality enhancement as well as advanced services for sentiment analysis, traffic jam estimation and trip recommendation based on estimated crowdedness. All developments are available under Open Source licenses (http://github.org/eubr-bigsea, https://hub.docker.com/u/eubrabigsea/)

NR/HEP: roadmap for the future

Physic in curved spacetime describes a multitude of phenomena, ranging from astrophysics to high-energy physics (HEP). The last few years have witnessed further progress on several fronts, including the accurate numerical evolution of the gravitational field equations, which now allows highly nonlinear phenomena to be tamed. Numerical relativity simulations, originally developed to understand strong-field astrophysical processes, could prove extremely useful to understand HEP processes such as trans-Planckian scattering and gauge-gravity dualities. We present a concise and comprehensive overview of the state-of-the-art and important open problems in the field(s), along with a roadmap for the next years

Towards Innovation Democracy? Participation, Responsibility and Precaution in Innovation Governance.

Innovation is about more than technological invention. It involves change of many kinds: cultural, organisational and behavioural as well as technological. So, in a world crying out for social justice and ecological care, innovation holds enormous progressive potential. Yet there are no guarantees that any particular realised innovation will necessarily be positive. Indeed, powerful forces ‘close down’ innovation in the directions favoured by the most privileged interests. So harnessing the positive transformative potential for innovation in any given area, is not about optimizing some single self-evidently progressive trajectory in a ‘race to the future’. Instead, it is about collaboratively exploring diverse and uncertain pathways – in ways that deliberately balance the spurious effects of incumbent power. In other words, what is needed is a more realistic, rational and vibrant ‘innovation democracy’