Parallel eigensolver operations are at the computational core of many large-scale scientific and engineering application codes. This project analyses parallel performance of established and newly developed parallel dense symmetric eigensolver numerical library routines on PRACE Tier-0 systems using real datasets from large-scale application codes. This whitepaper builds upon the research report ‘Dense Linear Algebra Performance Analysis on the Fujitsu BX900 OPL Machine†’ (from the same author) which can be found at: http://www.openpetascale.org/documents /2011_Dense_Linear_Algebra_Performance_Analysis_on_the_Fujitsu_BX900_OPL_Machine.pdf. This version of the report is updated with results from ScaLAPACK and with the recently released ELPA l...
HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facil...
textThis thesis demonstrates an efficient parallel method of solving the generalized eigenvalue prob...
We survey recent developments in dense numerical linear algebra, covering linear systems, least squa...
Parallel eigensolver operations are at the computational core of many large-scale scientific and eng...
MPP systems with a message-passing programming paradigm such as CRAY T3E still play an important rol...
For new exascale computers the degree of parallelismwill increase leading to architectures with more...
We discuss timing and performance modeling of a routine to find all the eigenvalues and eigenvectors...
Techniques for the vectorization and parallelization of a sequential code for evaluating, one at a t...
. In this paper, we present preliminary results on a complete eigensolver based on the Yau and Lu me...
With the invention of many-core systems like the Intel KNLstandard eigensolver libraries have to be ...
In the present work we describe HPEC (High Performance Eigenvalues Computation), a parallel software...
In this paper, we present the StarNEig library for solving dense nonsymmetric standard and generaliz...
In the present work we describe HPEC (High Performance Eigenvalues Computation), a parallel software...
SuperLU_DIST is a distributed memory parallel solver for sparse linear systems. The solver makes sev...
We investigate the performance of the routines in LAPACK and the Successive Band Reduction (SBR) too...
HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facil...
textThis thesis demonstrates an efficient parallel method of solving the generalized eigenvalue prob...
We survey recent developments in dense numerical linear algebra, covering linear systems, least squa...
Parallel eigensolver operations are at the computational core of many large-scale scientific and eng...
MPP systems with a message-passing programming paradigm such as CRAY T3E still play an important rol...
For new exascale computers the degree of parallelismwill increase leading to architectures with more...
We discuss timing and performance modeling of a routine to find all the eigenvalues and eigenvectors...
Techniques for the vectorization and parallelization of a sequential code for evaluating, one at a t...
. In this paper, we present preliminary results on a complete eigensolver based on the Yau and Lu me...
With the invention of many-core systems like the Intel KNLstandard eigensolver libraries have to be ...
In the present work we describe HPEC (High Performance Eigenvalues Computation), a parallel software...
In this paper, we present the StarNEig library for solving dense nonsymmetric standard and generaliz...
In the present work we describe HPEC (High Performance Eigenvalues Computation), a parallel software...
SuperLU_DIST is a distributed memory parallel solver for sparse linear systems. The solver makes sev...
We investigate the performance of the routines in LAPACK and the Successive Band Reduction (SBR) too...
HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facil...
textThis thesis demonstrates an efficient parallel method of solving the generalized eigenvalue prob...
We survey recent developments in dense numerical linear algebra, covering linear systems, least squa...