ESSEX - Equipping Sparse Solvers for Exascale

Drittmittelfinanzierte Gruppenförderung - Teilprojekt

Details zum übergeordneten Gesamtprojekt

Titel des Gesamtprojektes: SPP 1648: Software for Exascale Computing

Details zum Projekt

Prof. Dr. Gerhard Wellein
Dr. Georg Hager

Dominik Ernst

Beteiligte FAU-Organisationseinheiten:
Professur für Höchstleistungsrechnen
Regionales Rechenzentrum Erlangen (RRZE)

Mittelgeber: DFG / Schwerpunktprogramm (SPP)
Projektstart: 01.11.2012
Projektende: 30.06.2019


Hardwareeffiziente Bausteine für dünn besetzte lineare Algebra und stencil-basierten Verfahren
Professur für Höchstleistungsrechnen

Abstract (fachliche Beschreibung):

The ESSEX project investigates the computational issues arising for large scale sparse eigenvalue problems and develops programming concepts and numerical methods for their solution. The exascale challenges of extreme parallelism, energy efficiency, and resilience will be addressed by coherent software design between the three project layers which comprise building blocks, algorithms and applications. The MPI+X programming model, a holistic performance engineering strategy, and advanced fault tolerance mechanisms are the driving forces behind all developments. Classic Krylov, Jacobi-Davidson and recent FEAST methods will be enabled for exascale computing and equipped with advanced, scalable preconditioners. New implementations of domainspecific iterative schemes in physics and chemistry, namely the established Chebyshev expansion techniques for the computation of spectral properties and their novel extension to the time evolution of driven quantum systems, complement these algorithms.The software solutions of the ESSEX project will be combined into an Exascale Sparse Solver Repository (“ESSR”), where the specific demands of the quantum physics users are recognized by integration of quantum state encoding techniques at the fundamental level. The relevance of this project can then be demonstrated through application of the ESSR algorithms to graphene-based structures, topological insulators, and quantum Hall effect devices. Such studies require exascale resources together with modern numerical methods to determine many eigenstates at a given point of the spectrum of extremely large matrices or to compute an approximation to their full spectrum. The concepts, methods and software building blocks developed in the ESSEX project serve as general blueprints for other scientific application areas that depend on sparse iterative algorithms. The strong vertical interaction between all three project layers ensures that the user can quickly utilize any progress on the lower layers and immediately use the power of exascale machines once they become available.

Externe Partner

Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
Universität Greifswald
Bergische Universität Wuppertal
Technische Universität München (TUM)
Technische Universität Dresden


Kreutzer, M., Ernst, D., Bishop, A.R., Fehske, H., Hager, G., Nakajima, K., & Wellein, G. (2018). Chebyshev filter diagonalization on modern manycore processors and GPGPUs. Springer Verlag.
Anzt, H., Kreutzer, M., Ponce, E., Peterson, G.D., Wellein, G., & Dongarra, J. (2018). Optimization and performance evaluation of the IDR iterative Krylov solver on GPUs. International Journal of High Performance Computing Applications, 32(2), 220-230.

Zuletzt aktualisiert 2019-11-04 um 13:36