Section: Partnerships and Cooperations

European Initiatives

FP7 & H2020 Projects

  • Title: Parallel Numerical Linear Algebra for Future Extreme-Scale Systems

  • Programm: H2020

  • Duration: November 2015 - November 2018

  • Coordinator: UMEÅUniversitet

  • Partners:

    • Science and Technology Facilities Council (United Kingdom)

    • Computer Science Department, UmeåUniversitet (Sweden)

    • Mathematics Department, The University of Manchester (United Kingdom)

  • Inria contact: Laura Grigori

  • The NLAFET proposal is a direct response to the demands for new mathematical and algorithmic approaches for applications on extreme scale systems, as identified in the FETHPC work programme and call. This project will enable a radical improvement in the performance and scalability of a wide range of real-world applications relying on linear algebra software, by developing novel architecture-aware algorithms and software libraries, and the supporting runtime capabilities to achieve scalable performance and resilience on heterogeneous architectures. The focus is on a critical set of fundamental linear algebra operations including direct and iterative solvers for dense and sparse linear systems of equations and eigenvalue problems. Achieving this requires a co-design effort due to the characteristics and overwhelming complexity and immense scale of such systems. Recognized experts in algorithm design and theory, parallelism, and auto-tuning will work together to explore and negotiate the necessary tradeoffs. The main research objectives are: (i) development of novel algorithms that expose as much parallelism as possible, exploit heterogeneity, avoid communication bottlenecks, respond to escalating fault rates, and help meet emerging power constraints; (ii) exploration of advanced scheduling strategies and runtime systems focusing on the extreme scale and strong scalability in multi/many-core and hybrid environments; (iii) design and evaluation of novel strategies and software support for both offline and online auto-tuning. The validation and dissemination of results will be done by integrating new software solutions into challenging scientific applications in materials science, power systems, study of energy solutions, and data analysis in astrophysics. The deliverables also include a sustainable set of methods and tools for cross-cutting issues such as scheduling, auto-tuning, and algorithm-based fault tolerance packaged into open-source library modules.

  • Title: EXascale Algorithms and Advanced Computational Techniques

  • Programm: FP7

  • Duration: September 2013 - August 2016

  • Coordinator: IMEC

  • Partners:

    • Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V (Germany)

    • Interuniversitair Micro-Electronica Centrum Vzw (Belgium)

    • Intel Corporations (France)

    • Numerical Algorithms Group Ltd (United Kingdom)

    • T-Systems Solutions for Research (Germany)

    • Universiteit Antwerpen (Belgium)

    • Universita della Svizzera italiana (Switzerland)

    • Université de Versailles Saint-Quentin-En-Yvelines. (France)

    • Vysoka Skola Banska - Technicka Univerzita Ostrava (Czech Republic)

  • Inria contact: Luc Giraud

  • Numerical simulation is a crucial part of science and industry in Europe. The advancement of simulation as a discipline relies on increasingly compute intensive models that require more computational resources to run. This is the driver for the evolution to exascale. Due to limits in the increase in single processor performance, exascale machines will rely on massive parallelism on and off chip, with a complex hierarchy of resources. The large number of components and the machine complexity introduce severe problems for reliability and programmability. The former of these will require novel fault-aware algorithms and support software. In addition, the scale of the numerical models exacerbates the difficulties by making the use of more complex simulation algorithms necessary, for numerical stability reasons. A key example of this is increased reliance on solvers. Such solvers require global communication, which impacts scalability, and are often used with preconditioners, increasing complexity again. Unless there is a major rethink of the design of solver algorithms, their components and software structure, a large class of important numerical simulations will not scale beyond petascale. This in turn will hold back the development of European science and industry which will fail to reap the benefits from exascale. The EXA2CT project brings together experts at the cutting edge of the development of solvers, related algorithmic techniques, and HPC software architects for programming models and communication. It will take a revolutionary approach to exascale solvers and programming models, rather than the incremental approach of other projects. We will produce modular open source proto-applications that demonstrate the algorithms and programming techniques developed in the project, to help boot-strap the creation of genuine exascale codes.