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Parallel Numerical Linear Algebra for Future Extreme-Scale Systems

Parallel Numerical Linear Algebra for Future Extreme-Scale Systems

Objective

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.
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Coordinator

UMEA UNIVERSITET

Address

Universitetomradet
901 87 Umea

Sweden

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 1 207 500

Participants (4)

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THE UNIVERSITY OF MANCHESTER

United Kingdom

EU Contribution

€ 927 375

INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE

France

EU Contribution

€ 845 750

SCIENCE AND TECHNOLOGY FACILITIES COUNCIL

United Kingdom

UNITED KINGDOM RESEARCH AND INNOVATION

United Kingdom

EU Contribution

€ 926 750

Project information

Grant agreement ID: 671633

Status

Closed project

  • Start date

    1 November 2015

  • End date

    30 April 2019

Funded under:

H2020-EU.1.2.2.

  • Overall budget:

    € 3 907 375

  • EU contribution

    € 3 907 375

Coordinated by:

UMEA UNIVERSITET

Sweden