Oops. I was wondering what happened to my response, and I did not realize 
it was subject to approval and posted another 
attempt at framing the answer. Sorry.

On Tuesday, March 12, 2024 at 2:15:22 PM UTC-7 Petr Krysl wrote:

> Good point about  Tpetra: I will check it out.
>
> >  SparsityPattern is usually extremely fast
> If it is the only sequential of a program executed with multiple threads, 
> it can still control the scalability.
>
> Which reminds me: In your WorkStream paper, you do not report the time 
> taken to construct a sparsity pattern.
> Could you tell me how expensive it was compared to the sequential assembly 
> of the numbers into the matrix?
>
> Many thanks,
>
> Petr
>
> On Tuesday, March 12, 2024 at 12:08:29 PM UTC-7 bruno.t...@gmail.com 
> wrote:
>
>> In Trilinos, the Tpetra library has Graph which is basically a 
>> SparsityPattern. Tpetra uses Kokkos (which abstracts multithreading and GPU 
>> support) everywhere so I would expect that they use Kokkos to build the 
>> Graph too. Multithreading for dealii's SparsityPattern is not planned so 
>> far. It could be done but building the SparsityPattern is usually extremely 
>> fast compared to the rest of the code and so, it's not worth doing.
>>
>> Bruno
>>
>> Le mar. 12 mars 2024 à 14:17, Petr Krysl <krysl...@gmail.com> a écrit :
>>
>>> Thanks, that is a helpful confirmation.
>>> Would you know if there is any multithreading sparsity pattern 
>>> computation available anywhere?
>>> Is something like this planned for dealii?
>>>
>>> On Tuesday, March 12, 2024 at 10:39:22 AM UTC-7 bruno.t...@gmail.com 
>>> wrote:
>>>
>>>> Hello,
>>>>
>>>> SparsityPattern is used for deal.II own matrices which do not support 
>>>> MPI. As far as I can tell, SparsityPattern does not use multithreading and 
>>>> I don't think adding elements is threadsafe. So you are right.
>>>>
>>>> Best,
>>>>
>>>> Bruno
>>>>
>>>> On Tuesday, March 12, 2024 at 12:58:37 PM UTC-4 krysl...@gmail.com 
>>>> wrote:
>>>>
>>>>> It would appear that the sparsity pattern is not (and cannot be) 
>>>>> computed in parallel. That is my reading of the code. Am I wrong?
>>>>
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