ESSEX - Equipping Sparse Solvers for Exascale
Third Party Funds Group - Sub project
Start date : 01.11.2012
End date : 30.06.2019
Overall project details
Overall project
SPP 1648: Software for Exascale Computing
Project details
Scientific Abstract
Scientific Abstract
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.
