francisco.nieto's picture
Francisco Javier Nieto De Santos

Enabling future parallel applications


Our main objective is to enable the usage of this technology to optimize resources management by assigning adequate resources to the applications and dealing with non-functional aspects; facilitate access to resources, thanks to frontends which hide the complexity of HPC; create and adapt new tools able to use the parallel computation capabilities, especially in the field of parallel (real-time) data analytics; and research on new ways to perform parallel computation.


We are working towards the development of technologies of Exascale Computation for optimal resources management which enables the use of highly scalable applications avoiding bottlenecks while managing heterogeneous systems with accelerators; easing the use of HPC for different domains with tools for large and complex data analytics and parallelizing data processing to ease execution of experiments with a transparent access to HPC; and researching on future technologies such as New Quantum Computing and Future Neuromorphic Computing solutions.


We specialize in solving current issues when using HPC, and enabling the use of future exascale systems for smart orchestration of applications looking at several aspects (profiles, data movement, resources status, etc.), deriving some tasks to Cloud HPC resources whenever necessary; provision of front-ends for easy access and usage of HPC resources, integrating data management tools, experimentation tools, etc; and the development of the parallel Complex Event Processing engine for real-time data analysis, also available for low-power computing devices.



Edge and CLoud Computation: A Highly Distributed Software Architecture for Big Data AnalyticS
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Efficient distribution of big-data workloads along the compute continuum (from edge to cloud) while providing sound real-time guarantees on end-to-end data analytics responses


Centre of excellence for global systems science
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Advanced decision-support in the face of global challenges. It brings together the power of HPC and some of the most promising thinking on global systems in order to improve decisions in business, politics and civil society.


European e-Infrastructure for extreme data analytics in sustainable development
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Enabling users to fully benefit from underlying High Processing capacities to explore new methods, build new innovative services, perform predictions and simulations with extremely large and heterogeneous datasets.


Mathematical modelling, simulation, and optimization for societal challenges with scientific computing
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Bring HPC-as-a-Service to SMEs through a marketplace, validated through a series of experiments driven by SME's around their current needs, where non-HPC users are introduced to the technology with experts and HPC centers in fields like industry 4.0.


HPC and Big Data Technologies for Global Challenges
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Boost HPC-based simulations in global challenges, enabling the application and development of tools for agent-based simulations and HPDA, while applying AI techniques as a way to improve workflows and simulations which support decision making.


Mega modelling at runtime
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Scalable model-based framework for continuous development and runtime validation of complex systems.


Mathematical modelling, simulation and optimization for societal challenges with scientific computing
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Provision of an eInfrastructure focused on the optimized execution of Math Application Development Frameworks used in social science, done with a customized orchestration for OpenMP, MPI and large parallel applications.


Software Defined Application Infrastructures Management and Engineering
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Will provide tools to enable simpler and faster development, deployment, operation and execution, of heterogeneous applications in HPC, Cloud & Software defined environments.


Advanced research in automatic test generation, by pushing automation in DevOps one step further, and reusing existing assets to generate more test cases and configurations when the application is updated. It brings amplification services at unit level, configuration level and production stage.


Supporting evolution and adaptation of personalized software by exploiting contextual data and end-user feedback
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Feedback-driven approach for software life cycle management, with the ultimate purpose of improving users’ quality of experience.