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@ -39,23 +39,18 @@
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!
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!
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! This sample program solves a linear system obtained by discretizing a
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! This sample program solves a linear system obtained by discretizing a
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! PDE with Dirichlet BCs. The solver is CG, coupled with one of the
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! PDE with Dirichlet BCs. The solver is CG, coupled with one of the
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! following multi-level preconditioner, as explained in Section 4.1 of
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! following multi-level preconditioner, as explained in Section 4.2 of
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! the AMG4PSBLAS User's and Reference Guide:
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! the AMG4PSBLAS User's and Reference Guide:
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!
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!
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! - choice = 1, the default multi-level preconditioner solver, i.e.,
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! - choice = 1, a V-cycle with decoupled smoothed aggregation, 4 Jacobi
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! V-cycle with decoupled smoothed aggregation, 1 hybrid forward/backward
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! sweeps as pre/post-smoother and 8 Jacobi sweeps as coarsest-level
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! GS sweep as pre/post-smoother and UMFPACK as coarsest-level
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! solver with replicated coarsest matrix
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! solver (Sec. 4.1, Listing 1)
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!
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!
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! - choice = 2, a V-cycle preconditioner with 1 block-Jacobi sweep
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! - choice = 2, a W-cycle based on the coupled aggregation relying on matching,
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! (with ILU(0) on the blocks) as pre- and post-smoother, and 8 block-Jacobi
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! with maximum size of aggregates equal to 8 and smoothed prolongators,
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! sweeps (with ILU(0) on the blocks) as coarsest-level solver (Sec. 4.1, Listing 2)
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! 2 sweeps of Block-Jacobi ipre/post-smoother using approximate inverse INVK and
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!
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! 4 sweeps of Block-Jacobi with INVK as coarsest-level solver on distributed
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! - choice = 3, W-cycle preconditioner based on the coupled aggregation relying
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! coarsest matrix
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! on matching, with maximum size of aggregates equal to 8 and smoothed prolongators,
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! 2 hybrid forward/backward GS sweeps as pre/post-smoother, a distributed coarsest
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! matrix, and preconditioned Flexible Conjugate Gradient as coarsest-level solver
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! (Sec. 4.1, Listing 3)
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!
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!
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! The matrix and the rhs are read from files (if an rhs is not available, the
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! The matrix and the rhs are read from files (if an rhs is not available, the
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! unit rhs is set).
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! unit rhs is set).
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@ -183,8 +178,9 @@ program amg_dexample_gpu
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case(1)
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case(1)
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! initialize a V-cycle preconditioner with 4 Jacobi sweep
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! initialize a V-cycle preconditioner, relying on decoupled smoothed aggregation
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! and 8 Jacobi sweeps as coarsest-level solver
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! with 4 Jacobi sweeps as pre/post-smoother
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! and 8 Jacobi sweeps as coarsest-level solver on replicated coarsest matrix
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call P%init(ctxt,'ML',info)
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call P%init(ctxt,'ML',info)
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call P%set('SMOOTHER_TYPE','JACOBI',info)
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call P%set('SMOOTHER_TYPE','JACOBI',info)
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@ -195,19 +191,22 @@ program amg_dexample_gpu
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case(2)
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case(2)
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! initialize a V-cycle preconditioner based on the coupled aggregation relying on matching,
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! initialize a W-cycle preconditioner based on the coupled aggregation relying on matching,
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! with maximum size of aggregates equal to 8 and smoothed prolongators,
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! with maximum size of aggregates equal to 8 and smoothed prolongators,
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! Block-Jacobi smoother using approximate inverse INVK and
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! 2 sweeps of Block-Jacobi pre/post-smoother using approximate inverse INVK and
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! and 4 sweeps of INVK on he coarsest level
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! 4 sweeps of Block-Jacobi with INVK on the coarsest level distributed matrix
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call P%init(ctxt,'ML',info)
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call P%init(ctxt,'ML',info)
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call P%set('PAR_AGGR_ALG','COUPLED',info)
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call P%set('PAR_AGGR_ALG','COUPLED',info)
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call P%set('AGGR_TYPE','MATCHBOXP',info)
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call P%set('AGGR_TYPE','MATCHBOXP',info)
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call P%set('AGGR_SIZE',8,info)
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call P%set('AGGR_SIZE',8,info)
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call P%set('ML_CYCLE','WCYCLE',info)
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call P%set('ML_CYCLE','WCYCLE',info)
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call P%set('SMOOTHER_TYPE','BJAC',info)
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call P%set('SMOOTHER_SWEEPS',2,info)
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call P%set('SMOOTHER_SWEEPS',2,info)
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call P%set('SUB_SOLVE','INVK',info)
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call P%set('SUB_SOLVE','INVK',info)
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call P%set('COARSE_SOLVE','INVK',info)
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call P%set('COARSE_SOLVE','BJAC',info)
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call P%set('COARSE_SUBSOLVE','INVK',info)
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call P%set('COARSE_SWEEPS',4,info)
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call P%set('COARSE_MAT','DIST',info)
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call P%set('COARSE_MAT','DIST',info)
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kmethod = 'CG'
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kmethod = 'CG'
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Salvatore Filippone
4 years ago