[petsc-users] memory use of a DMDA

Barry Smith bsmith at mcs.anl.gov
Mon Oct 21 11:32:53 CDT 2013


   The PETSc DMDA object greedily allocates several arrays of data used to set up the communication and other things like local to global mappings even before you create any vectors. This is why you see this big bump in memory usage.

   BUT I don't think it should be any worse in 3.4 than in 3.3 or earlier; at least we did not intend to make it worse. Are you sure it is using more memory than in 3.3

   In order for use to decrease the memory usage of the DMDA setup it would be helpful if we knew which objects created within it used the most memory.  There is some sloppiness in that routine of not reusing memory as well as could be, not sure how much difference that would make.


   Barry



On Oct 21, 2013, at 7:02 AM, Juha Jäykkä <juhaj at iki.fi> wrote:

> Dear list members,
> 
> I have noticed strange memory consumption after upgrading to 3.4 series. I 
> never had time to properly investigate, but here is what happens [yes, this 
> might be a petsc4py issue, but I doubt it] is
> 
> # helpers contains _ProcessMemoryInfoProc routine which just digs the memory
> # usage data from /proc
> import helpers
> procdata=helpers._ProcessMemoryInfoProc()
> print procdata.rss/2**20, "MiB /", procdata.os_specific[3][1]
> from petsc4py import PETSc
> procdata=helpers._ProcessMemoryInfoProc()
> print procdata.rss/2**20, "MiB /", procdata.os_specific[3][1]
> da = PETSc.DA().create(sizes=[100,100,100],
>                       proc_sizes=[PETSc.DECIDE,PETSc.DECIDE,PETSc.DECIDE],
>                       boundary_type=[3,0,0],
>                       stencil_type=PETSc.DA.StencilType.BOX,
>                       dof=7, stencil_width=1, comm=PETSc.COMM_WORLD)
> procdata=helpers._ProcessMemoryInfoProc()
> print procdata.rss/2**20, "MiB /", procdata.os_specific[3][1]
> vec=da.createGlobalVec()
> procdata=helpers._ProcessMemoryInfoProc()
> print procdata.rss/2**20, "MiB /", procdata.os_specific[3][1]
> 
> outputs
> 
> 48 MiB / 49348 kB
> 48 MiB / 49360 kB
> 381 MiB / 446228 kB
> 435 MiB / 446228 kB
> 
> Which is odd: size of the actual data to be stored in the da is just about 56 
> megabytes, so why does creating the da consume 7 times that? And why does the 
> DA reserve the memory in the first place? I thought memory only gets allocated 
> once an associated vector is created and it indeed looks like the 
> createGlobalVec call does indeed allocate the right amount of data. But what 
> is that 330 MiB that DA().create() consumes? [It's actually the .setUp() 
> method that does the consuming, but that's not of much use as it needs to be 
> called before a vector can be created.]
> 
> Cheers,
> Juha
> 



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