Sanjay,
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
With OpenMPI,
mpirun -n 4 ./ex5 -da_grid_x 128 -da_grid_y 128 -ts_type beuler
-ts_max_steps 500 > 128.log
grep -n -v "RSS Delta= 0, Malloc Delta= 0" 128.log
1:RSS Delta= 69632, Malloc Delta= 0
2:RSS Delta= 69632, Malloc Delta= 0
3:RSS Delta= 69632, Malloc Delta= 0
4:RSS Delta= 69632, Malloc Delta= 0
9:RSS Delta=9.25286e+06, Malloc Delta= 0
22:RSS Delta= 49152, Malloc Delta= 0
44:RSS Delta= 20480, Malloc Delta= 0
53:RSS Delta= 49152, Malloc Delta= 0
66:RSS Delta= 4096, Malloc Delta= 0
97:RSS Delta= 16384, Malloc Delta= 0
119:RSS Delta= 20480, Malloc Delta= 0
141:RSS Delta= 53248, Malloc Delta= 0
176:RSS Delta= 16384, Malloc Delta= 0
308:RSS Delta= 16384, Malloc Delta= 0
352:RSS Delta= 16384, Malloc Delta= 0
550:RSS Delta= 16384, Malloc Delta= 0
572:RSS Delta= 16384, Malloc Delta= 0
669:RSS Delta= 40960, Malloc Delta= 0
924:RSS Delta= 32768, Malloc Delta= 0
1694:RSS Delta= 20480, Malloc Delta= 0
2099:RSS Delta= 16384, Malloc Delta= 0
2244:RSS Delta= 20480, Malloc Delta= 0
3001:RSS Delta= 16384, Malloc Delta= 0
5883:RSS Delta= 16384, Malloc Delta= 0
If I increased the grid
mpirun -n 4 ./ex5 -da_grid_x 512 -da_grid_y 512 -ts_type beuler
-ts_max_steps 500 -malloc_test >512.log
grep -n -v "RSS Delta= 0, Malloc Delta= 0" 512.log
1:RSS Delta=1.05267e+06, Malloc Delta= 0
2:RSS Delta=1.05267e+06, Malloc Delta= 0
3:RSS Delta=1.05267e+06, Malloc Delta= 0
4:RSS Delta=1.05267e+06, Malloc Delta= 0
13:RSS Delta=1.24932e+08, Malloc Delta= 0
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?
On Thu, May 30, 2019 at 1:59 PM Smith, Barry F. <bsm...@mcs.anl.gov
<mailto:bsm...@mcs.anl.gov>> wrote:
Thanks for the update. So the current conclusions are that
using the Waitall in your code
1) solves the memory issue with OpenMPI in your code
2) does not solve the memory issue with PETSc KSPSolve
3) MPICH has memory issues both for your code and PETSc KSPSolve
(despite) the wait all fix?
If you literately just comment out the call to KSPSolve() with
OpenMPI is there no growth in memory usage?
Both 2 and 3 are concerning, indicate possible memory leak bugs in
MPICH and not freeing all MPI resources in KSPSolve()
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
Barry
> On May 30, 2019, at 1:47 PM, Sanjay Govindjee <s...@berkeley.edu
<mailto:s...@berkeley.edu>> wrote:
>
> Lawrence,
> Thanks for taking a look! This is what I had been wondering
about -- my knowledge of MPI is pretty minimal and
> this origins of the routine were from a programmer we hired a
decade+ back from NERSC. I'll have to look into
> VecScatter. It will be great to dispense with our roll-your-own
routines (we even have our own reduceALL scattered around the code).
>
> Interestingly, the MPI_WaitALL has solved the problem when using
OpenMPI but it still persists with MPICH. Graphs attached.
> 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;
> I'll try Barry's suggestion of
--download-mpich-configure-arguments="--enable-error-messages=all
--enable-g" later today and report back).
>
> Regarding MPI_Barrier, it was put in due a problem that some
processes were finishing up sending and receiving and exiting the
subroutine
> 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
> to us. I don't think I can dispense with it, but will think
about some more.
>
> I'm not so sure about using MPI_IRecv as it will require a bit
of rewriting since right now I process the received
> data sequentially after each blocking MPI_Recv -- clearly slower
but easier to code.
>
> Thanks again for the help.
>
> -sanjay
>
> On 5/30/19 4:48 AM, Lawrence Mitchell wrote:
>> Hi Sanjay,
>>
>>> On 30 May 2019, at 08:58, Sanjay Govindjee via petsc-users
<petsc-users@mcs.anl.gov <mailto:petsc-users@mcs.anl.gov>> wrote:
>>>
>>> The problem seems to persist but with a different signature.
Graphs attached as before.
>>>
>>> Totals with MPICH (NB: single run)
>>>
>>> For the CG/Jacobi data_exchange_total = 41,385,984;
kspsolve_total = 38,289,408
>>> For the GMRES/BJACOBI data_exchange_total = 41,324,544;
kspsolve_total = 41,324,544
>>>
>>> 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?
>>> I would have thought that with the blocking receives and the
MPI_Barrier that everything will have fully completed and cleaned
up before
>>> all processes exited the routine, but perhaps I am wrong on that.
>>
>> Skimming the fortran code you sent you do:
>>
>> for i in ...:
>> call MPI_Isend(..., req, ierr)
>>
>> for i in ...:
>> call MPI_Recv(..., ierr)
>>
>> 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.
>>
>> The usual pattern for these non-blocking communications is to
allocate an array for the requests of length nsend+nrecv and then do:
>>
>> for i in nsend:
>> call MPI_Isend(..., req[i], ierr)
>> for j in nrecv:
>> call MPI_Irecv(..., req[nsend+j], ierr)
>>
>> call MPI_Waitall(req, ..., ierr)
>>
>> 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.
>>
>> As an aside, is there a reason you don't use PETSc's VecScatter
to manage this global to local exchange?
>>
>> Cheers,
>>
>> Lawrence
>
> <cg_mpichwall.png><cg_wall.png><gmres_mpichwall.png><gmres_wall.png>
