Barcelona Supercomputing Center

Barcelona, Spain

Barcelona Supercomputing Center

Barcelona, Spain
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Grant
Agency: European Commission | Branch: H2020 | Program: ERA-NET-Cofund | Phase: SC5-02-2015 | Award Amount: 78.28M | Year: 2016

Within the European Research Area (ERA), the ERA4CS Consortium is aiming to boost, research for Climate Services (CS), including climate adaptation, mitigation and disaster risk management, allowing regions, cities and key economic sectors to develop opportunities and strengthen Europes leadership. CS are seen by this consortium as driven by user demands to provide knowledge to face impacts of climate variability and change, as well as guidance both to researchers and decisionmakers in policy and business. ERA4CS will focus on the development of a climate information translation layer bridging user communities and climate system sciences. It implies the development of tools, methods, standards and quality control for reliable, qualified and tailored information required by the various field actors for smart decisions. ERA4CS will boost the JPI Climate initiative by mobilizing more countries, within EU Member States and Associated Countries, by involving both the research performing organizations (RPOs) and the research funding organizations (RFOs), the distinct national climate services and the various disciplines of academia, including Social Sciences and Humanities. ERA4CS will launch a joint transnational co-funded call, with over 16 countries and up to 75M, with two complementary topics: (i) a cash topic, supported by 12 RFOs, on co-development for user needs and action-oriented projects; (ii) an in-kind topic, supported by 28 RPOs, on institutional integration of the research components of national CS. Finally, ERA4CS additional activities will initiate a strong partnership between JPI Climate and others key European and international initiatives (as Copernicus, KIC-Climate, JPIs, WMO/GFCS, Future Earth, Belmont Forum) in order to work towards a common vision and a multiyear implementation strategy, including better co-alignment of national programs and activities up to 2020 and beyond.


Grant
Agency: European Commission | Branch: H2020 | Program: SGA-RIA | Phase: FETFLAGSHIP | Award Amount: 89.00M | Year: 2016

Understanding the human brain is one of the greatest scientific challenges of our time. Such an understanding can provide profound insights into our humanity, leading to fundamentally new computing technologies, and transforming the diagnosis and treatment of brain disorders. Modern ICT brings this prospect within reach. The HBP Flagship Initiative (HBP) thus proposes a unique strategy that uses ICT to integrate neuroscience data from around the world, to develop a unified multi-level understanding of the brain and diseases, and ultimately to emulate its computational capabilities. The goal is to catalyze a global collaborative effort. During the HBPs first Specific Grant Agreement (SGA1), the HBP Core Project will outline the basis for building and operating a tightly integrated Research Infrastructure, providing HBP researchers and the scientific Community with unique resources and capabilities. Partnering Projects will enable independent research groups to expand the capabilities of the HBP Platforms, in order to use them to address otherwise intractable problems in neuroscience, computing and medicine in the future. In addition, collaborations with other national, European and international initiatives will create synergies, maximizing returns on research investment. SGA1 covers the detailed steps that will be taken to move the HBP closer to achieving its ambitious Flagship Objectives.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: BG-09-2016 | Award Amount: 15.49M | Year: 2016

The overall objective of INTAROS is to develop an integrated Arctic Observation System (iAOS) by extending, improving and unifying existing systems in the different regions of the Arctic. INTAROS will have a strong multidisciplinary focus, with tools for integration of data from atmosphere, ocean, cryosphere and terrestrial sciences, provided by institutions in Europe, North America and Asia. Satellite earth observation data plays an increasingly important role in such observing systems, because the amount of EO data for observing the global climate and environment grows year by year. In situ observing systems are much more limited due to logistical constraints and cost limitations. The sparseness of in situ data is therefore the largest gap in the overall observing system. INTAROS will assess strengths and weaknesses of existing observing systems and contribute with innovative solutions to fill some of the critical gaps in the in situ observing network. INTAROS will develop a platform, iAOS, to search for and access data from distributed databases. The evolution into a sustainable Arctic observing system requires coordination, mobilization and cooperation between the existing European and international infrastructures (in-situ and remote including space-based), the modeling communities and relevant stakeholder groups. INTAROS will include development of community-based observing systems, where local knowledge is merged with scientific data. An integrated Arctic Observation System will enable better-informed decisions and better-documented processes within key sectors (e.g. local communities, shipping, tourism, fisheries), in order to strengthen the societal and economic role of the Arctic region and support the EU strategy for the Arctic and related maritime and environmental policies.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: EINFRA-11-2016 | Award Amount: 16.11M | Year: 2017

PRACE, the Partnership for Advanced Computing is the permanent pan-European High Performance Computing service providing world-class systems for world-class science. Systems at the highest performance level (Tier-0) are deployed by Germany, France, Italy and Spain providing researchers with over 11 billion core hours of compute time. HPC experts from 25 member states enabled users from academia and industry to ascertain leadership and remain competitive in the Global Race. Currently PRACE is in transition to PRACE 2, the successor of the initial five year period. The objectives of PRACE-5IP are to build on and seamlessly continue the successes of PRACE and start new innovative and collaborative activities proposed by the consortium. These include: assisting the transition to PRACE 2 including an analysis of Trans National Access; strengthening the internationally recognised PRACE brand; continuing and extend advanced training which so far provided more than 18 800 persontraining days; preparing strategies and best practices towards Exascale computing; coordinating and enhancing the operation of the multi-tier HPC systems and services; and supporting users to exploit massively parallel systems and novel architectures. A high level Service Catalogue is provided. The proven project structure will be used to achieve each of the objectives in 6 dedicated work packages. The activities are designed to increase Europes research and innovation potential especially through: seamless and efficient Tier-0 services and a pan-European HPC ecosystem including national capabilities; promoting take-up by industry and new communities and special offers to SMEs; implementing a new flexible business model for PRACE 2; proposing strategies for deployment of leadership systems; collaborating with the ETP4HPC, CoEs and other European and international organisations on future architectures, training, application support and policies. This will be monitored through a set of KPIs.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: INFRADEV-04-2016 | Award Amount: 9.95M | Year: 2017

The EOSCpilot project will support the first phase in the development of the European Open Science Cloud (EOSC) as described in the EC Communication on European Cloud Initiatives [2016]. It will establish the governance framework for the EOSC and contribute to the development of European open science policy and best practice; It will develop a number of pilots that integrate services and infrastructures to demonstrate interoperability in a number of scientific domains; and It will engage with a broad range of stakeholders, crossing borders and communities, to build the trust and skills required for adoption of an open approach to scientific research . These actions will build on and leverage already available resources and capabilities from research infrastructure and e-infrastructure organisations to maximise their use across the research community. The EOSCpilot project will address some of the key reasons why European research is not yet fully tapping into the potential of data. In particular, it will: reduce fragmentation between data infrastructures by working across scientific and economic domains, countries and governance models, and improve interoperability between data infrastructures by demonstrating how data and resources can be shared even when they are large and complex and in varied formats, In this way, the EOSC pilot project will improve the ability to reuse data resources and provide an important step towards building a dependable open-data research environment where data from publicly funded research is always open and there are clear incentives and rewards for the sharing of data and resources.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: FCT-01-2015 | Award Amount: 11.99M | Year: 2016

ASGARD has a singular goal, contribute to Law Enforcement Agencies Technological Autonomy and effective use of technology. Technologies will be transferred to end users under an open source scheme focusing on Forensics, Intelligence and Foresight (Intelligence led prevention and anticipation). ASGARD will drive progress in the processing of seized data, availability of massive amounts of data and big data solutions in an ever more connected world. New areas of research will also be addressed. The consortium is configured with LEA end users and practitioners pulling from the Research and Development community who will push transfer of knowledge and innovation. A Community of LEA users is the end point of ASGARD with the technology as a focal point for cooperation (a restricted open source community). In addition to traditional Use Cases and trials, in keeping with open source concepts and continuous integration approaches, ASGARD will use Hackathons to demonstrate its results. Vendor lock-in is addressed whilst also recognising their role and existing investment by LEAs. The project will follow a cyclical approach for early results. Data Set, Data Analytics (multimodal/ multimedia), Data Mining and Visual Analytics are included in the work plan. Technologies will be built under the maxim of It works over Its the best. Rapid adoption/flexible deployment strategies are included. The project includes a licensing and IPR approach coherent with LEA realities and Ethical needs. ASGARD includes a comprehensive approach to Privacy, Ethics, Societal Impact respecting fundamental rights. ASGARD leverages existing trust relationship between LEAs and the research and development industry, and experiential knowledge in FCT research. ASGARD will allow its community of users leverage the benefits of agile methodologies, technology trends and open source approaches that are currently exploited by the general ICT sector and Organised Crime and Terrorist organisations.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-06-2016 | Award Amount: 5.44M | Year: 2017

Fog computing brings cloud computing capabilities closer to the end-device and users, while enabling location-dependent resource allocation, low latency services, and extending significantly the IoT services portfolio as well as market and business opportunities in the cloud sector. With the number of devices exponentially growing globally, new cloud and fog models are expected to emerge, paving the way for shared, collaborative, extensible mobile, volatile and dynamic compute, storage and network infrastructure. When put together, cloud and fog computing create a new stack of resources, which we refer to as Fog-to-Cloud (F2C), creating the need for a new, open and coordinated management ecosystem. The mF2C proposal sets the goal of designing an open, secure, decentralized, multi-stakeholder management framework, including novel programming models, privacy and security, data storage techniques, service creation, brokerage solutions, SLA policies, and resource orchestration methods. The proposed framework is expected to set the foundations for a novel distributed system architecture, developing a proof-of-concept system and platform, to be tested and validated in real-world use cases, as envisioned by the industrial partners in the consortium with significant interest in rapid innovation in the cloud computing sector.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: BG-10-2016 | Award Amount: 8.72M | Year: 2016

Arctic climate change increases the need of a growing number of stakeholders for trustworthy weather and climate predictions, both within the Arctic and beyond. APPLICATE will address this challenge and develop enhanced predictive capacity by bringing together scientists from academia, research institutions and operational prediction centres, including experts in weather and climate prediction and forecast dissemination. APPLICATE will develop a comprehensive framework for observationally constraining and assessing weather and climate models using advanced metrics and diagnostics. This framework will be used to establish the performance of existing models and measure the progress made within the project. APPLICATE will make significant model improvements, focusing on aspects that are known to play pivotal roles in both weather and climate prediction, namely: the atmospheric boundary layer including clouds; sea ice; snow; atmosphere-sea ice-ocean coupling; and oceanic transports. In addition to model developments, APPLICATE will enhance predictive capacity by contributing to the design of the future Arctic observing system and through improved forecast initialization techniques. The impact of Arctic climate change on the weather and climate of the Northern Hemisphere through atmospheric and oceanic linkages will be determined by a comprehensive set of novel multi-model numerical experiments using both coupled and uncoupled ocean and atmosphere models. APPLICATE will develop strong user-engagement and dissemination activities, including pro-active engagement of end-users and the exploitation of modern methods for communication and dissemination. Knowledge-transfer will also benefit from the direct engagement of operational prediction centres in APPLICATE. The educational component of APPLICATE will be developed and implemented in collaboration with the Association of Early Career Polar Scientists (APECS).


Madadkar-Sobhani A.,Barcelona Supercomputing Center
Nucleic acids research | Year: 2013

PELE, Protein Energy Landscape Exploration, our novel technology based on protein structure prediction algorithms and a Monte Carlo sampling, is capable of modelling the all-atom protein-ligand dynamical interactions in an efficient and fast manner, with two orders of magnitude reduced computational cost when compared with traditional molecular dynamics techniques. PELE's heuristic approach generates trial moves based on protein and ligand perturbations followed by side chain sampling and global/local minimization. The collection of accepted steps forms a stochastic trajectory. Furthermore, several processors may be run in parallel towards a collective goal or defining several independent trajectories; the whole procedure has been parallelized using the Message Passing Interface. Here, we introduce the PELE web server, designed to make the whole process of running simulations easier and more practical by minimizing input file demand, providing user-friendly interface and producing abstract outputs (e.g. interactive graphs and tables). The web server has been implemented in C++ using Wt (http://www.webtoolkit.eu) and MySQL (http://www.mysql.com). The PELE web server, accessible at http://pele.bsc.es, is free and open to all users with no login requirement.


Grant
Agency: European Commission | Branch: H2020 | Program: ERC-STG | Phase: ERC-2016-STG | Award Amount: 1.48M | Year: 2017

The accuracy obtained in wind tunnel aerodynamic and aero-acoustic measurements is extremely demanding and it still challenges our current simulation technologies. It mainly challenges the capabilities of current mesh generation technologies used in flow simulations. The ground-breaking TESSERACT project addresses the challenge of studying how to generate computational meshes that enable the ability to obtain computer flow simulations that beat the predictive capabilities of the wind tunnel experiments for a fixed accuracy, cost, and time scale. These important challenges correspond to capabilities that have been considered essential to fulfil the European strategic goals of future transportation. The main objective is to generate optimal quality curved adapted meshes for space-time flow simulations by addressing the following ambitious and beyond the state of the art 4-dimensional meshing research objectives: curved geometry representation and approximation, mesh quality measures, adapted mesh resolution, and space-time flow simulation. This is a high risk project since it tackles meshing objectives in 4D while lower dimension versions of these issues have not yet been fully solved. However, providing the foundations and the methods to improve current space-time meshing algorithms will suppose a high gain in the field of computational and aerospace engineering. This is so since in the near future, it will be of major importance to conduct accurate, robust, and efficient parallel in space-time adapted flow simulations that exploit the computational power of the exascale super-computing facilities to come. To enhance the feasibility of the project, the scientific approach considers different novel approaches to reach the same objectives and therefore, bear in mind the high-risk / high-gain nature of this 4D meshing project.

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