[petsc-users] Can't expand MemType 1: jcol 16104
Xiaoye S. Li
xsli at lbl.gov
Tue Jul 7 17:58:40 CDT 2015
Is there an inquiry function that tells you all the available options?
Sherry
On Tue, Jul 7, 2015 at 3:25 PM, Anthony Paul Haas <aph at email.arizona.edu>
wrote:
> Hi Sherry,
>
> Thanks for your message. I have used superlu_dist default options. I did
> not realize that I was doing serial symbolic factorization. That is
> probably the cause of my problem.
> Each node on Garnet has 60GB usable memory and I can run with 1,2,4,8,16
> or 32 core per node.
>
> So I should use:
>
> -mat_superlu_dist_r 20
> -mat_superlu_dist_c 32
>
> How do you specify the parallel symbolic factorization option? is it
> -mat_superlu_dist_matinput 1
>
> Thanks,
>
> Anthony
>
>
> On Tue, Jul 7, 2015 at 3:08 PM, Xiaoye S. Li <xsli at lbl.gov> wrote:
>
>> For superlu_dist failure, this occurs during symbolic factorization.
>> Since you are using serial symbolic factorization, it requires the entire
>> graph of A to be available in the memory of one MPI task. How much memory
>> do you have for each MPI task?
>>
>> It won't help even if you use more processes. You should try to use
>> parallel symbolic factorization option.
>>
>> Another point. You set up process grid as:
>> Process grid nprow 32 x npcol 20
>> For better performance, you show swap the grid dimension. That is, it's
>> better to use 20 x 32, never gives nprow larger than npcol.
>>
>>
>> Sherry
>>
>>
>> On Tue, Jul 7, 2015 at 1:27 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
>>
>>>
>>> I would suggest running a sequence of problems, 101 by 101 111 by 111
>>> etc and get the memory usage in each case (when you run out of memory you
>>> can get NO useful information out about memory needs). You can then plot
>>> memory usage as a function of problem size to get a handle on how much
>>> memory it is using. You can also run on more and more processes (which
>>> have a total of more memory) to see how large a problem you may be able to
>>> reach.
>>>
>>> MUMPS also has an "out of core" version (which we have never used)
>>> that could in theory anyways let you get to large problems if you have lots
>>> of disk space, but you are on your own figuring out how to use it.
>>>
>>> Barry
>>>
>>> > On Jul 7, 2015, at 2:37 PM, Anthony Paul Haas <aph at email.arizona.edu>
>>> wrote:
>>> >
>>> > Hi Jose,
>>> >
>>> > In my code, I use once PETSc to solve a linear system to get the
>>> baseflow (without using SLEPc) and then I use SLEPc to do the stability
>>> analysis of that baseflow. This is why, there are some SLEPc options that
>>> are not used in test.out-superlu_dist-151x151 (when I am solving for the
>>> baseflow with PETSc only). I have attached a 101x101 case for which I get
>>> the eigenvalues. That case works fine. However If i increase to 151x151, I
>>> get the error that you can see in test.out-superlu_dist-151x151 (similar
>>> error with mumps: see test.out-mumps-151x151 line 2918 ). If you look a the
>>> very end of the files test.out-superlu_dist-151x151 and
>>> test.out-mumps-151x151, you will see that the last info message printed is:
>>> >
>>> > On Processor (after EPSSetFromOptions) 0 memory:
>>> 0.65073152000E+08 =====> (see line 807 of module_petsc.F90)
>>> >
>>> > This means that the memory error probably occurs in the call to
>>> EPSSolve (see module_petsc.F90 line 810). I would like to evaluate how much
>>> memory is required by the most memory intensive operation within EPSSolve.
>>> Since I am solving a generalized EVP, I would imagine that it would be the
>>> LU decomposition. But is there an accurate way of doing it?
>>> >
>>> > Before starting with iterative solvers, I would like to exploit as
>>> much as I can direct solvers. I tried GMRES with default preconditioner at
>>> some point but I had convergence problem. What solver/preconditioner would
>>> you recommend for a generalized non-Hermitian (EPS_GNHEP) EVP?
>>> >
>>> > Thanks,
>>> >
>>> > Anthony
>>> >
>>> > On Tue, Jul 7, 2015 at 12:17 AM, Jose E. Roman <jroman at dsic.upv.es>
>>> wrote:
>>> >
>>> > El 07/07/2015, a las 02:33, Anthony Haas escribió:
>>> >
>>> > > Hi,
>>> > >
>>> > > I am computing eigenvalues using PETSc/SLEPc and superlu_dist for
>>> the LU decomposition (my problem is a generalized eigenvalue problem). The
>>> code runs fine for a grid with 101x101 but when I increase to 151x151, I
>>> get the following error:
>>> > >
>>> > > Can't expand MemType 1: jcol 16104 (and then [NID 00037]
>>> 2015-07-06 19:19:17 Apid 31025976: OOM killer terminated this process.)
>>> > >
>>> > > It seems to be a memory problem. I monitor the memory usage as far
>>> as I can and it seems that memory usage is pretty low. The most memory
>>> intensive part of the program is probably the LU decomposition in the
>>> context of the generalized EVP. Is there a way to evaluate how much memory
>>> will be required for that step? I am currently running the debug version of
>>> the code which I would assume would use more memory?
>>> > >
>>> > > I have attached the output of the job. Note that the program uses
>>> twice PETSc: 1) to solve a linear system for which no problem occurs, and,
>>> 2) to solve the Generalized EVP with SLEPc, where I get the error.
>>> > >
>>> > > Thanks
>>> > >
>>> > > Anthony
>>> > > <test.out-superlu_dist-151x151>
>>> >
>>> > In the output you are attaching there are no SLEPc objects in the
>>> report and SLEPc options are not used. It seems that SLEPc calls are
>>> skipped?
>>> >
>>> > Do you get the same error with MUMPS? Have you tried to solve linear
>>> systems with a preconditioned iterative solver?
>>> >
>>> > Jose
>>> >
>>> >
>>> >
>>> <module_petsc.F90><test.out-mumps-151x151><test.out_superlu_dist-101x101><test.out-superlu_dist-151x151>
>>>
>>>
>>
>
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