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Software and Performance Engineering for Iterative Eigensolvers

Thies, Jonas (2017) Software and Performance Engineering for Iterative Eigensolvers. PASC 2017, 26.-28.6.2017, Lugano, Schweiz.

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The complexity of the latest HPC architectures increasingly limits the productivity of researchers in numerical algorithms and the `time to market' for parallel algorithms. Implementing a new method on a supercomputer today involves at least three levels of parallelism and typically several programming models like MPI, OpenMP and CUDA. Frameworks like Trilinos and PETSc have since many years been useful for testing new ideas in parallel algorithms. But when it comes to e.g. CPU/GPU clusters they fail to deliver convincing performance to date. We look at sparse solvers from a software engineer's point of view and advocate a programming model we call `SPMD+OK', introducing performance models in the test-driven development process and a strategy to facilitate the integration of algorithmic developments into existing applications. Harnessing the peta-scale with the block Jacobi-Davidson method is used as a running example in this talk, and the libraries GHOST and PHIST are presented (https://bitbucket.org/essex/).

Item URL in elib:https://elib.dlr.de/118977/
Document Type:Conference or Workshop Item (Speech)
Title:Software and Performance Engineering for Iterative Eigensolvers
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Date:27 June 2017
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:high performance computing, heterogenous Hardware, sparse matrices, eigenproblems, Performance modelling
Event Title:PASC 2017
Event Location:Lugano, Schweiz
Event Type:international Conference
Event Dates:26.-28.6.2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Vorhaben SISTEC (old)
Location: Köln-Porz
Institutes and Institutions:Institut of Simulation and Software Technology > High Performance Computing
Deposited By: Thies, Jonas
Deposited On:22 Feb 2018 14:52
Last Modified:31 Jul 2019 20:16

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