DEEP-EST
Verkefnanúmer: 754304
Lengd verkefnis: 45 mánuðir (1. júl 2017 - 31. mar 2021)
Heildarkostnaður: €15.365.546
Evrópustyrkur: €14.998.342 (€312.860 veittur Háskóla Íslands)
Styrkur í samræmi við: H2020-EU.1.2.2. - FET Proactive
Verkefnastýring: Forschungszentrum Jülich GmBh, Þýskalandi
Vefsíða: https://www.deep-projects.eu/
The DEEP-EST (“DEEP - Extreme Scale Technologies”) project will create a first incarnation of the Modular Supercomputer Architecture (MSA) and demonstrate its benefits.
In the spirit of the DEEP and DEEP-ER projects, the MSA integrates compute modules with different performance characteristics into a single heterogeneous system. Each module is a parallel, clustered system of potentially large size. A federated network connects the module-specific interconnects. MSA brings substantial benefits for heterogeneous applications/workflows: each part can be run on an exactly matching system, improving time to solution and energy use. This is ideal for supercomputer centres running heterogeneous application mixes (higher throughput and energy efficiency). It also offers valuable flexibility to the compute providers, allowing the set of modules and their respective size to be tailored to actual usage.
The DEEP-EST prototype will include three modules: general purpose Cluster Module and Extreme Scale Booster supporting the full range of HPC applications, and Data Analytics Module specifically designed for high-performance data analytics (HPDA) workloads. Proven programming models and APIs from HPC (combining MPI and OmpSs) and HPDA will be extended and combined with a significantly enhanced resource management and scheduling system to enable straightforward use of the new architecture and achieve highest system utilisation and performance.
Scalability projections will be given up to the Exascale performance class. The DEEP-EST prototype will be defined in close co-design between applications, system software and system component architects. Its implementation will employ European integration, network and software technologies. Six ambitious and highly relevant European applications from HPC and HPDA domains will drive the co-design, serving to evaluate the DEEP EST prototype and demonstrate the benefits of its innovative Modular Supercomputer Architecture.
H2020-EU.1.2. - EXCELLENT SCIENCE - Future and Emerging Technologies (FET)
The specific objective is to foster radically new technologies with the potential to open new fields for scientific knowledge and technologies and contribute to the European next generation industries, by exploring novel and high-risk ideas building on scientific foundations. By providing flexible support to goal-oriented and interdisciplinary collaborative research on various scales and by adopting innovative research practices, the aim is to identify and seize opportunities of long-term benefit for citizens, the economy and society. FET will bring Union added value to the frontiers of modern research.
FET shall promote research and technology beyond what is known, accepted or widely adopted and shall foster novel and visionary thinking to open promising paths towards powerful new technologies, some of which could develop into leading technological and intellectual paradigms for the decades ahead. FET shall foster efforts to pursue small-scale research opportunities across all areas, including emerging themes and grand scientific and technological challenges that require close collaboration between programmes across Europe and beyond. This approach shall be driven by excellence and extends to exploring pre-competitive ideas for shaping the future of technology, enabling society and industry to benefit from multi-disciplinary research collaboration that needs to be engaged at European level by making the link between research driven by science and research driven by societal goals and challenges or by industrial competitiveness.
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Þátttakendur
Helmut Wolfram Neukirchen | Prófessor | 6152554 | helmut [hjá] hi.is | Yes | https://iris.rais.is/is/persons/70225861-0156-4e08-b61f-3cd82ac0c574 | Iðnaðarverkfræði-, vélaverkfræði- og tölvunarfræðideild, kennsla |
Morris Riedel | Prófessor | morris [hjá] hi.is | https://iris.rais.is/is/persons/b63278df-f63a-4b42-83c0-dbe521395c5f | Iðnaðarverkfræði-, vélaverkfræði- og tölvunarfræðideild, kennsla |