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Auto select memory-efficient algorithms for HMG #16210

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fdkong opened this issue Nov 16, 2020 · 0 comments · Fixed by #16213
Closed

Auto select memory-efficient algorithms for HMG #16210

fdkong opened this issue Nov 16, 2020 · 0 comments · Fixed by #16213
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C: Framework P: normal A defect affecting operation with a low possibility of significantly affects. T: task An enhancement to the software.

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@fdkong
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fdkong commented Nov 16, 2020

Reason

HMG is a high-performance (hybrid) MG preconditioner that uses HYPRE to coarsen matrix and PETSc PCs as the smoothers. It is able to reuse interpolation and restriction matrices of one moose variable for all other nonlinear moose variables. Use interpolation and restriction matrices to form coarse matrices requires memory-efficient algorithms. The default algorithms in PETSc generate unexpected memory spikes. We need to use new algorithms "allatonce".

Design

Automatically apply PtAP algorithms when users use HMG.

Impact

Reduce memory usage for large scale problems

@fdkong fdkong added T: task An enhancement to the software. P: normal A defect affecting operation with a low possibility of significantly affects. labels Nov 16, 2020
fdkong added a commit to fdkong/moose that referenced this issue Nov 16, 2020
fdkong added a commit to fdkong/moose that referenced this issue Nov 16, 2020
fdkong added a commit to fdkong/moose that referenced this issue Dec 2, 2020
fdkong added a commit to fdkong/moose that referenced this issue Dec 2, 2020
jain651 pushed a commit to jain651/moose that referenced this issue Apr 19, 2021
jain651 pushed a commit to jain651/moose that referenced this issue Apr 19, 2021
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Labels
C: Framework P: normal A defect affecting operation with a low possibility of significantly affects. T: task An enhancement to the software.
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