It may be a good idea to combine this study with looking at the output
of -log_summary (assuming PETSc is your solver engine) to see if there
is a correlation with the growth in communication or other components
of matrix assembly.
Dmitry.

On Mon, Jun 10, 2013 at 10:16 AM, Ataollah Mesgarnejad
<[email protected]> wrote:
> Cody,
>
> I'm not sure if you saw the graph I uploaded it again here: 
> https://dl.dropboxusercontent.com/u/19391830/scaling.jpg.
>
> In all these runs the NDOFs/Processor is less than 10000. What is bothering 
> me is that the enforce_constraints_exactly is taking up more and more time as 
> number of processor grows for the same problem.
>
> Now I can think of an explanation that the NDOFs/Processor is so low that the 
> communication time is becoming a problem! That said my main concern is that 
> I'm using the DirichletBCs API badly and that results in bad scaling.
>
> PS: Sorry for multiple copies I forgot to CC libMesh user list.
>
> Best,
> Ata
> On Jun 10, 2013, at 9:48 AM, Cody Permann <[email protected]> wrote:
>
>> Ata,
>>
>> You might be scaling past the reasonable limit for libMesh.  I don't know 
>> what solver you are using, but for a strong scaling study we generally don't 
>> go below 10,000 local DOFs.  This is the recommended floor for PETSc too:
>> http://www.mcs.anl.gov/petsc/documentation/faq.html#slowerparallel
>>
>> Before you start drawing conclusions about scaling, you might start with a 
>> bigger problem and see if it scales well to the ~20,000 local DOF range.
>>
>> Cody
>>
>>
>>
>> On Mon, Jun 10, 2013 at 8:42 AM, Ataollah Mesgarnejad 
>> <[email protected]> wrote:
>> Dear all,
>>
>> I've been doing some scaling  tests on my code. When I look at time (or % of 
>> time) spent at each stage in libMesh log I see that the 
>> enforce_constraints_exactly stage in DofMap is scaling very bad. I was 
>> wondering if anyone can comment.
>>
>> Here is my EquationSystems.print_info():
>>
>> EquationSystems
>>   n_systems()=2
>>    System #0, "elasticity_system"
>>     Type "TransientLinearImplicit"
>>     Variables={ "u" "v" }
>>     Finite Element Types="LAGRANGE", "JACOBI_20_00"
>>     Infinite Element Mapping="CARTESIAN"
>>     Approximation Orders="FIRST", "THIRD"
>>     n_dofs()=48660
>>     n_local_dofs()=930
>>     n_constrained_dofs()=1048
>>     n_local_constrained_dofs()=56
>>     n_vectors()=3
>>     n_matrices()=1
>>     DofMap Sparsity
>>       Average  On-Processor Bandwidth <= 13.6478
>>       Average Off-Processor Bandwidth <= 0.904233
>>       Maximum  On-Processor Bandwidth <= 20
>>       Maximum Off-Processor Bandwidth <= 16
>>     DofMap Constraints
>>       Number of DoF Constraints = 1048
>>       Average DoF Constraint Length= 0
>>       Number of Node Constraints = 0
>>    System #1, "fracture_system"
>>     Type "TransientNonlinearImplicit"
>>     Variables="psi"
>>     Finite Element Types="LAGRANGE", "JACOBI_20_00"
>>     Infinite Element Mapping="CARTESIAN"
>>     Approximation Orders="FIRST", "THIRD"
>>     n_dofs()=24330
>>     n_local_dofs()=465
>>     n_constrained_dofs()=167
>>     n_local_constrained_dofs()=0
>>     n_vectors()=3
>>     n_matrices()=1
>>     DofMap Sparsity
>>       Average  On-Processor Bandwidth <= 6.82388
>>       Average Off-Processor Bandwidth <= 0.452117
>>       Maximum  On-Processor Bandwidth <= 10
>>       Maximum Off-Processor Bandwidth <= 8
>>     DofMap Constraints
>>       Number of DoF Constraints = 167
>>       Average DoF Constraint Length= 0
>>       Number of Node Constraints = 0
>>
>>
>> and here is the how scaling looks for every stage that took > 1% of time:
>>
>>
>>
>> Best,
>> Ata
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