Thanks Hong, I am not seeing these options with -help ...
On Wed, May 3, 2017 at 10:05 PM, Hong <[email protected]> wrote: > I basically used 'runex56' and set '-ne' be compatible with np. > Then I used option > '-matptap_via scalable' > '-matptap_via hypre' > '-matptap_via nonscalable' > > I attached a job script below. > > In master branch, I set default as 'nonscalable' for small - medium size > matrices, and automatically switch to 'scalable' when matrix size gets > larger. > > Petsc solver uses MatPtAP, which does local RAP to reduce communication > and accelerate computation. > I suggest you simply use default setting. Let me know if you encounter > trouble. > > Hong > > job.ne174.n8.np125.sh: > runjob --np 125 -p 16 --block $COBALT_PARTNAME --verbose=INFO : ./ex56 -ne > 174 -alpha 1.e-3 -ksp_type cg -pc_type gamg -pc_gamg_agg_nsmooths 1 > -pc_gamg_reuse_interpolation true -ksp_converged_reason > -use_mat_nearnullspace -mg_levels_esteig_ksp_type cg > -mg_levels_esteig_ksp_max_it 10 -pc_gamg_square_graph 1 > -mg_levels_ksp_max_it 1 -mg_levels_ksp_type chebyshev > -mg_levels_ksp_chebyshev_esteig 0,0.2,0,1.05 -gamg_est_ksp_type cg > -gamg_est_ksp_max_it 10 -pc_gamg_asm_use_agg true -mg_levels_sub_pc_type lu > -mg_levels_pc_asm_overlap 0 -pc_gamg_threshold -0.01 > -pc_gamg_coarse_eq_limit 200 -pc_gamg_process_eq_limit 30 > -pc_gamg_repartition false -pc_mg_cycle_type v > -pc_gamg_use_parallel_coarse_grid_solver > -mg_coarse_pc_type jacobi -mg_coarse_ksp_type cg -ksp_monitor -log_view > -matptap_via scalable > log.ne174.n8.np125.scalable > > runjob --np 125 -p 16 --block $COBALT_PARTNAME --verbose=INFO : ./ex56 -ne > 174 -alpha 1.e-3 -ksp_type cg -pc_type gamg -pc_gamg_agg_nsmooths 1 > -pc_gamg_reuse_interpolation true -ksp_converged_reason > -use_mat_nearnullspace -mg_levels_esteig_ksp_type cg > -mg_levels_esteig_ksp_max_it 10 -pc_gamg_square_graph 1 > -mg_levels_ksp_max_it 1 -mg_levels_ksp_type chebyshev > -mg_levels_ksp_chebyshev_esteig 0,0.2,0,1.05 -gamg_est_ksp_type cg > -gamg_est_ksp_max_it 10 -pc_gamg_asm_use_agg true -mg_levels_sub_pc_type lu > -mg_levels_pc_asm_overlap 0 -pc_gamg_threshold -0.01 > -pc_gamg_coarse_eq_limit 200 -pc_gamg_process_eq_limit 30 > -pc_gamg_repartition false -pc_mg_cycle_type v > -pc_gamg_use_parallel_coarse_grid_solver > -mg_coarse_pc_type jacobi -mg_coarse_ksp_type cg -ksp_monitor -log_view > -matptap_via hypre > log.ne174.n8.np125.hypre > > runjob --np 125 -p 16 --block $COBALT_PARTNAME --verbose=INFO : ./ex56 -ne > 174 -alpha 1.e-3 -ksp_type cg -pc_type gamg -pc_gamg_agg_nsmooths 1 > -pc_gamg_reuse_interpolation true -ksp_converged_reason > -use_mat_nearnullspace -mg_levels_esteig_ksp_type cg > -mg_levels_esteig_ksp_max_it 10 -pc_gamg_square_graph 1 > -mg_levels_ksp_max_it 1 -mg_levels_ksp_type chebyshev > -mg_levels_ksp_chebyshev_esteig 0,0.2,0,1.05 -gamg_est_ksp_type cg > -gamg_est_ksp_max_it 10 -pc_gamg_asm_use_agg true -mg_levels_sub_pc_type lu > -mg_levels_pc_asm_overlap 0 -pc_gamg_threshold -0.01 > -pc_gamg_coarse_eq_limit 200 -pc_gamg_process_eq_limit 30 > -pc_gamg_repartition false -pc_mg_cycle_type v > -pc_gamg_use_parallel_coarse_grid_solver > -mg_coarse_pc_type jacobi -mg_coarse_ksp_type cg -ksp_monitor -log_view > -matptap_via nonscalable > log.ne174.n8.np125.nonscalable > > runjob --np 125 -p 16 --block $COBALT_PARTNAME --verbose=INFO : ./ex56 -ne > 174 -alpha 1.e-3 -ksp_type cg -pc_type gamg -pc_gamg_agg_nsmooths 1 > -pc_gamg_reuse_interpolation true -ksp_converged_reason > -use_mat_nearnullspace -mg_levels_esteig_ksp_type cg > -mg_levels_esteig_ksp_max_it 10 -pc_gamg_square_graph 1 > -mg_levels_ksp_max_it 1 -mg_levels_ksp_type chebyshev > -mg_levels_ksp_chebyshev_esteig 0,0.2,0,1.05 -gamg_est_ksp_type cg > -gamg_est_ksp_max_it 10 -pc_gamg_asm_use_agg true -mg_levels_sub_pc_type lu > -mg_levels_pc_asm_overlap 0 -pc_gamg_threshold -0.01 > -pc_gamg_coarse_eq_limit 200 -pc_gamg_process_eq_limit 30 > -pc_gamg_repartition false -pc_mg_cycle_type v > -pc_gamg_use_parallel_coarse_grid_solver > -mg_coarse_pc_type jacobi -mg_coarse_ksp_type cg -ksp_monitor -log_view > > log.ne174.n8.np125 > > On Wed, May 3, 2017 at 2:08 PM, Mark Adams <[email protected]> wrote: > >> Hong,the input files do not seem to be accessible. What are the command >> line option? (I don't see a "rap" or "scale" in the source). >> >> >> >> On Wed, May 3, 2017 at 12:17 PM, Hong <[email protected]> wrote: >> >>> Mark, >>> Below is the copy of my email sent to you on Feb 27: >>> >>> I implemented scalable MatPtAP and did comparisons of three >>> implementations using ex56.c on alcf cetus machine (this machine has >>> small memory, 1GB/core): >>> - nonscalable PtAP: use an array of length PN to do dense axpy >>> - scalable PtAP: do sparse axpy without use of PN array >>> - hypre PtAP. >>> >>> The results are attached. Summary: >>> - nonscalable PtAP is 2x faster than scalable, 8x faster than hypre PtAP >>> - scalable PtAP is 4x faster than hypre PtAP >>> - hypre uses less memory (see job.ne399.n63.np1000.sh) >>> >>> Based on above observation, I set the default PtAP algorithm as >>> 'nonscalable'. >>> When PN > local estimated nonzero of C=PtAP, then switch default to >>> 'scalable'. >>> User can overwrite default. >>> >>> For the case of np=8000, ne=599 (see job.ne599.n500.np8000.sh), I get >>> MatPtAP 3.6224e+01 (nonscalable for small mats, >>> scalable for larger ones) >>> scalable MatPtAP 4.6129e+01 >>> hypre 1.9389e+02 >>> >>> This work in on petsc-master. Give it a try. If you encounter any >>> problem, let me know. >>> >>> Hong >>> >>> On Wed, May 3, 2017 at 10:01 AM, Mark Adams <[email protected]> wrote: >>> >>>> (Hong), what is the current state of optimizing RAP for scaling? >>>> >>>> Nate, is driving 3D elasticity problems at scaling with GAMG and we are >>>> working out performance problems. They are hitting problems at ~1.5B dof >>>> problems on a basic Cray (XC30 I think). >>>> >>>> Thanks, >>>> Mark >>>> >>> >>> >> >
