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<div dir="ltr" class="gmail_attr">On Sat, Jun 1, 2019 at 3:21 AM Sanjay Govindjee <<a href="mailto:s_g@berkeley.edu">s_g@berkeley.edu</a>> wrote:<br>
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<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
Barry,<br>
<br>
If you look at the graphs I generated (on my Mac), you will see that <br>
OpenMPI and MPICH have very different values (along with the fact that <br>
MPICH does not seem to adhere<br>
to the standard (for releasing MPI_ISend resources following and MPI_Wait).<br>
<br>
-sanjay <br>
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<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
PS: I agree with Barry's assessment; this is really not that acceptable.<br>
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<div>I also agree. I am doing various experiments to know why. </div>
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<br>
On 6/1/19 1:00 AM, Smith, Barry F. wrote:<br>
> Junchao,<br>
><br>
> This is insane. Either the OpenMPI library or something in the OS underneath related to sockets and interprocess communication is grabbing additional space for each round of MPI communication! Does MPICH have the same values or different values than
OpenMP? When you run on Linux do you get the same values as Apple or different. --- Same values seem to indicate the issue is inside OpenMPI/MPICH different values indicates problem is more likely at the OS level. Does this happen only with the default VecScatter
that uses blocking MPI, what happens with PetscSF under Vec? Is it somehow related to PETSc's use of nonblocking sends and receives? One could presumably use valgrind to see exactly what lines in what code are causing these increases. I don't think we can
just shrug and say this is the way it is, we need to track down and understand the cause (and if possible fix).<br>
><br>
> Barry<br>
><br>
><br>
>> On May 31, 2019, at 2:53 PM, Zhang, Junchao <<a href="mailto:jczhang@mcs.anl.gov" target="_blank">jczhang@mcs.anl.gov</a>> wrote:<br>
>><br>
>> Sanjay,<br>
>> I tried petsc with MPICH and OpenMPI on my Macbook. I inserted PetscMemoryGetCurrentUsage/PetscMallocGetCurrentUsage at the beginning and end of KSPSolve and then computed the delta and summed over processes. Then I tested with src/ts/examples/tutorials/advection-diffusion-reaction/ex5.c<br>
>> With OpenMPI,<br>
>> mpirun -n 4 ./ex5 -da_grid_x 128 -da_grid_y 128 -ts_type beuler -ts_max_steps 500 > 128.log<br>
>> grep -n -v "RSS Delta= 0, Malloc Delta= 0" 128.log<br>
>> 1:RSS Delta= 69632, Malloc Delta= 0<br>
>> 2:RSS Delta= 69632, Malloc Delta= 0<br>
>> 3:RSS Delta= 69632, Malloc Delta= 0<br>
>> 4:RSS Delta= 69632, Malloc Delta= 0<br>
>> 9:RSS Delta=9.25286e+06, Malloc Delta= 0<br>
>> 22:RSS Delta= 49152, Malloc Delta= 0<br>
>> 44:RSS Delta= 20480, Malloc Delta= 0<br>
>> 53:RSS Delta= 49152, Malloc Delta= 0<br>
>> 66:RSS Delta= 4096, Malloc Delta= 0<br>
>> 97:RSS Delta= 16384, Malloc Delta= 0<br>
>> 119:RSS Delta= 20480, Malloc Delta= 0<br>
>> 141:RSS Delta= 53248, Malloc Delta= 0<br>
>> 176:RSS Delta= 16384, Malloc Delta= 0<br>
>> 308:RSS Delta= 16384, Malloc Delta= 0<br>
>> 352:RSS Delta= 16384, Malloc Delta= 0<br>
>> 550:RSS Delta= 16384, Malloc Delta= 0<br>
>> 572:RSS Delta= 16384, Malloc Delta= 0<br>
>> 669:RSS Delta= 40960, Malloc Delta= 0<br>
>> 924:RSS Delta= 32768, Malloc Delta= 0<br>
>> 1694:RSS Delta= 20480, Malloc Delta= 0<br>
>> 2099:RSS Delta= 16384, Malloc Delta= 0<br>
>> 2244:RSS Delta= 20480, Malloc Delta= 0<br>
>> 3001:RSS Delta= 16384, Malloc Delta= 0<br>
>> 5883:RSS Delta= 16384, Malloc Delta= 0<br>
>><br>
>> If I increased the grid<br>
>> mpirun -n 4 ./ex5 -da_grid_x 512 -da_grid_y 512 -ts_type beuler -ts_max_steps 500 -malloc_test >512.log<br>
>> grep -n -v "RSS Delta= 0, Malloc Delta= 0" 512.log<br>
>> 1:RSS Delta=1.05267e+06, Malloc Delta= 0<br>
>> 2:RSS Delta=1.05267e+06, Malloc Delta= 0<br>
>> 3:RSS Delta=1.05267e+06, Malloc Delta= 0<br>
>> 4:RSS Delta=1.05267e+06, Malloc Delta= 0<br>
>> 13:RSS Delta=1.24932e+08, Malloc Delta= 0<br>
>><br>
>> So we did see RSS increase in 4k-page sizes after KSPSolve. As long as no memory leaks, why do you care about it? Is it because you run out of memory?<br>
>><br>
>> On Thu, May 30, 2019 at 1:59 PM Smith, Barry F. <<a href="mailto:bsmith@mcs.anl.gov" target="_blank">bsmith@mcs.anl.gov</a>> wrote:<br>
>><br>
>> Thanks for the update. So the current conclusions are that using the Waitall in your code<br>
>><br>
>> 1) solves the memory issue with OpenMPI in your code<br>
>><br>
>> 2) does not solve the memory issue with PETSc KSPSolve<br>
>><br>
>> 3) MPICH has memory issues both for your code and PETSc KSPSolve (despite) the wait all fix?<br>
>><br>
>> If you literately just comment out the call to KSPSolve() with OpenMPI is there no growth in memory usage?<br>
>><br>
>><br>
>> Both 2 and 3 are concerning, indicate possible memory leak bugs in MPICH and not freeing all MPI resources in KSPSolve()<br>
>><br>
>> Junchao, can you please investigate 2 and 3 with, for example, a TS example that uses the linear solver (like with -ts_type beuler)? Thanks<br>
>><br>
>><br>
>> Barry<br>
>><br>
>><br>
>><br>
>>> On May 30, 2019, at 1:47 PM, Sanjay Govindjee <<a href="mailto:s_g@berkeley.edu" target="_blank">s_g@berkeley.edu</a>> wrote:<br>
>>><br>
>>> Lawrence,<br>
>>> Thanks for taking a look! This is what I had been wondering about -- my knowledge of MPI is pretty minimal and<br>
>>> this origins of the routine were from a programmer we hired a decade+ back from NERSC. I'll have to look into<br>
>>> VecScatter. It will be great to dispense with our roll-your-own routines (we even have our own reduceALL scattered around the code).<br>
>>><br>
>>> Interestingly, the MPI_WaitALL has solved the problem when using OpenMPI but it still persists with MPICH. Graphs attached.<br>
>>> I'm going to run with openmpi for now (but I guess I really still need to figure out what is wrong with MPICH and WaitALL;<br>
>>> I'll try Barry's suggestion of --download-mpich-configure-arguments="--enable-error-messages=all --enable-g" later today and report back).<br>
>>><br>
>>> Regarding MPI_Barrier, it was put in due a problem that some processes were finishing up sending and receiving and exiting the subroutine<br>
>>> before the receiving processes had completed (which resulted in data loss as the buffers are freed after the call to the routine). MPI_Barrier was the solution proposed<br>
>>> to us. I don't think I can dispense with it, but will think about some more.<br>
>>><br>
>>> I'm not so sure about using MPI_IRecv as it will require a bit of rewriting since right now I process the received<br>
>>> data sequentially after each blocking MPI_Recv -- clearly slower but easier to code.<br>
>>><br>
>>> Thanks again for the help.<br>
>>><br>
>>> -sanjay<br>
>>><br>
>>> On 5/30/19 4:48 AM, Lawrence Mitchell wrote:<br>
>>>> Hi Sanjay,<br>
>>>><br>
>>>>> On 30 May 2019, at 08:58, Sanjay Govindjee via petsc-users <<a href="mailto:petsc-users@mcs.anl.gov" target="_blank">petsc-users@mcs.anl.gov</a>> wrote:<br>
>>>>><br>
>>>>> The problem seems to persist but with a different signature. Graphs attached as before.<br>
>>>>><br>
>>>>> Totals with MPICH (NB: single run)<br>
>>>>><br>
>>>>> For the CG/Jacobi data_exchange_total = 41,385,984; kspsolve_total = 38,289,408<br>
>>>>> For the GMRES/BJACOBI data_exchange_total = 41,324,544; kspsolve_total = 41,324,544<br>
>>>>><br>
>>>>> Just reading the MPI docs I am wondering if I need some sort of MPI_Wait/MPI_Waitall before my MPI_Barrier in the data exchange routine?<br>
>>>>> I would have thought that with the blocking receives and the MPI_Barrier that everything will have fully completed and cleaned up before<br>
>>>>> all processes exited the routine, but perhaps I am wrong on that.<br>
>>>> Skimming the fortran code you sent you do:<br>
>>>><br>
>>>> for i in ...:<br>
>>>> call MPI_Isend(..., req, ierr)<br>
>>>><br>
>>>> for i in ...:<br>
>>>> call MPI_Recv(..., ierr)<br>
>>>><br>
>>>> But you never call MPI_Wait on the request you got back from the Isend. So the MPI library will never free the data structures it created.<br>
>>>><br>
>>>> The usual pattern for these non-blocking communications is to allocate an array for the requests of length nsend+nrecv and then do:<br>
>>>><br>
>>>> for i in nsend:<br>
>>>> call MPI_Isend(..., req[i], ierr)<br>
>>>> for j in nrecv:<br>
>>>> call MPI_Irecv(..., req[nsend+j], ierr)<br>
>>>><br>
>>>> call MPI_Waitall(req, ..., ierr)<br>
>>>><br>
>>>> I note also there's no need for the Barrier at the end of the routine, this kind of communication does neighbourwise synchronisation, no need to add (unnecessary) global synchronisation too.<br>
>>>><br>
>>>> As an aside, is there a reason you don't use PETSc's VecScatter to manage this global to local exchange?<br>
>>>><br>
>>>> Cheers,<br>
>>>><br>
>>>> Lawrence<br>
>>> <cg_mpichwall.png><cg_wall.png><gmres_mpichwall.png><gmres_wall.png><br>
<br>
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