Elap: Difference between revisions
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The ELPA project has been started in 2008 with the aim to support the then uppcoming Petaflop HPC systems (the acronym originates from the German expression “Eigenwert Löser für Petaflop Anwendungen”; in English “Eigenvalue Solvers for Petaflop Applications”). During the last decade the ELPA-library has proven to provide highly efficient eigenvalue solvers for Petaflop systems. Nowadays, with (pre)-Exascale systems on the horizon, although keeping its well established name, the ELPA-library targets the Exascale range. The development of the ELPA-library has been supported by BMBF grants 01IH08007 (Dec. 2008 - Nov. 2011) and 01IH15001 (Feb. 2016 - Jan. 2019). During Oct. 2020 until April 2024 the development of the ELPA library has been supported by the European Center of Excellence project Nomad CoE. | |||
Though especially designed for the use case of solving large problem sizes on massively parallel supercomputers, ELPA eigensolvers have proven to be also very efficient for smaller matric | |||
DESCRIPTION | DESCRIPTION | ||
Revision as of 12:55, 12 March 2025
Description
ELAP website
The ELPA project has been started in 2008 with the aim to support the then uppcoming Petaflop HPC systems (the acronym originates from the German expression “Eigenwert Löser für Petaflop Anwendungen”; in English “Eigenvalue Solvers for Petaflop Applications”). During the last decade the ELPA-library has proven to provide highly efficient eigenvalue solvers for Petaflop systems. Nowadays, with (pre)-Exascale systems on the horizon, although keeping its well established name, the ELPA-library targets the Exascale range. The development of the ELPA-library has been supported by BMBF grants 01IH08007 (Dec. 2008 - Nov. 2011) and 01IH15001 (Feb. 2016 - Jan. 2019). During Oct. 2020 until April 2024 the development of the ELPA library has been supported by the European Center of Excellence project Nomad CoE.
Though especially designed for the use case of solving large problem sizes on massively parallel supercomputers, ELPA eigensolvers have proven to be also very efficient for smaller matric DESCRIPTION
Environment Modules
Run module spider ELAP to find out what environment modules are available for this application.
System Variables
- HPC_ELAP_DIR - installation directory