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@MISC{Baumeister:1028638,
author = {Baumeister, Paul and Nassyr, Stepan and Li, Yanlong},
title = {tf{QMR}gpu v0.9 - a header-only {GPU}-accelerated iterative
linear solver for multiple right-hand sides},
reportid = {FZJ-2024-04705},
year = {2023},
abstract = {tfQMRgpu is a C++ header-only library written in CUDA.
Version 0.9 aims to offer the transpose-free Quasi Minimal
Residual method for the iterative solving of linear problems
with multiple right-hand sides using graphical processors
(GPUs).The library is shipped with the default use case of
complex block-sparse operators with a set of available block
sizes to be selected before compilation. C-interfaces expose
the APIs for both, single precision (float) and double
precision, to be called from other programming languages
such as C, Fortran, Julia or Python.The block-sparse matrix
solver version can be linked as shared object
tfQMRgpu.so.The header-only feature allows to provide a
custom C++/CUDA action operators to
$tfQMRgpu::solve<action_t>$ and compiles with the host
code.},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511)},
pid = {G:(DE-HGF)POF4-5111},
typ = {PUB:(DE-HGF)33},
doi = {10.5281/ZENODO.8333498},
url = {https://juser.fz-juelich.de/record/1028638},
}