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Auflistung nach Autor:in "Eicker, Norbert"

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  • Zeitschriftenartikel
    The DEEP-SEA project: a software stack for heterogeneous and modular supercomputers
    (PARS-Mitteilungen: Vol. 36, 2024) Suarez, Estela; Eicker, Norbert; Hoppe, Hans-Christian
    Today’s most powerful supercomputers achieve their performance through heterogeneous system architectures that integrate CPUs with accelerators, especially GPUs, and advanced multi-level memory systems. This hardware diversity challenges application developers to adapt legacy code, requiring significant efforts in code evolution and optimisation. The European DEEP-SEA project has developed an integrated software stack for heterogeneous HPC systems, including kernel modules, libraries, management systems and programming abstractions. It supports heterogeneous hardware configurations including modular supercomputers, enabling optimal resource allocation, application of malleability and programming model composability. Enhanced tools and data placement policies improved performance on DRAM and fast memory. Results were made publicly available, ensuring sustainability through integration with upstream open source projects and extension of HPC standards. This paper summarises the DEEP-SEA project’s contributions to a wide variety of software packages and developments.
  • Zeitschriftenartikel
    Particle-in-Cell algorithms on DEEP: The iPiC3D case study
    (PARS-Mitteilungen: Vol. 32, Nr. 1, 2015) Jakobs, Anna; Zitz, Anke; Eicker, Norbert; Lapenta, Giovanni
    The DEEP (Dynamical Exascale Entry Platform) project aims to provide a first implementation of a novel architecture for heterogeneous high-performance computing. This architecture consists of a standard HPC Cluster and – tightly coupled – a cluster of many-core processors called Booster. This concept offers application developers the opportunity to run different parts of their program on the best fitting part of the machine striving for an optimal overall performance. In order to take advantage of this architecture applications require some adaption. To provide optimal support to the application developers the DEEP concept includes a high-level programming model that helps to separate a given program to the Cluster and Booster parts of the DEEP System. This paper presents the adaption work required for a Particle-in-Cell space weather application developed by KULeuven (Katholieke Universiteit Leuven) done in the course of the DEEP project. It discusses all crucial steps of the work starting with a scalability analysis of the different parts of the program, their performance projections for the Cluster and the Booster leading to the separation decisions for the application and finally the actual implementation work. In addition to that some performance results are presented.