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fix an error when choosing the Nvidia GPU kernel (fallback to CPU might have
been selected)
support of Nvidia cusolver library to accelerate some routines (needs CUDA >= 11.4)
experimental Nvidia GPU versions for "elpa_invert_trm" and "elpa_cholesky"
can be tested by setting elpa_set("gpu_invert_trm",1) and
elpa_set("gpu_cholesky",1). Is not used otherwise
BUGFIX: error in resort_ev (also backported to 2021.05.002 and 2020.11.001)
allow to call ELPA eigenvectors and eigenvalues also with GPU device
pointers for the input matrix, the vectors of eigenvalues and the output
matrix for the eigenvectors
BUGFIX: error in resort_ev
EXPERIMENTAL feature:g new real GPU kernel for Nvidia A100 (provided by Nvidia): can show a
performance boost if number of vectors per MPI task is > 20000. Most likely
most benifit in non-MPI version
as anounced, droping the legacy interface
more autotuning features, for example using non blocking MPI collectives
new version of autotunig avoiding a combinatorial grow of possibilities
(the old autotune version can be still used if
elpa%autotune_set_api_version(API_VERSION, error) is set to API_VERSION <
20211125)