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 Civil-Comp Proceedings 
ISSN 1759-3433 CCP: 111 
PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING Edited by: P. Iványi, B.H.V. Topping and G. Várady 
Paper 9 
Wavelet Based Deflation of Conjugate Gradient Method J. Kruzik and D. Horak  
1IT4Innovations, VSB-Technical University of Ostrava, Czech Republic
 Full Bibliographic Reference for this paper 
J. Kruzik, D. Horak , "Wavelet Based Deflation of Conjugate Gradient Method", in P. Iványi, B.H.V. Topping, G. Várady, (Editors), "Proceedings of the
Fifth International Conference
on
Parallel, Distributed, Grid and Cloud Computing
for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 9, 2017. doi:10.4203/ccp.111.9 
Keywords: deflation, projected preconditioning, conjugate gradient, deflated conjugate
gradient, wavelet compression, coarse problem, Krylov subspace. 
Summary 
This paper introduces a Krylov subspace deflation technique based on a discretewavelet
compression. This technique is based on an observation that the deflation coarse problem
matrix is closely related to a matrix obtained by a discrete wavelet transformation.
Thanks to this observation, we know exactly how the deflation space should look like.
Moreover, we can directly and cheaply assemble this space. We showcase both numerical
and performance aspects of our approach on the deflated conjugate gradient
method. However, our findings should be also valid for other deflated Krylov subspace
methods, like GMRES or MINRES.
 
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