[petsc-dev] MatMult on Summit
Mark Adams
mfadams at lbl.gov
Mon Sep 23 17:53:30 CDT 2019
Note, the numerical problems that we have look a lot like a race condition
of some sort. Happens with empty processors and goes away under
cuda-memcheck (valgrind like thing).
I did try adding WaitForGPU() , but maybe I did do it right or there are
other synchronization mechanisms.
On Mon, Sep 23, 2019 at 6:28 PM Zhang, Junchao via petsc-dev <
petsc-dev at mcs.anl.gov> wrote:
> It looks cusparsestruct->stream is always created (not NULL). I don't
> know logic of the "if (!cusparsestruct->stream)".
> --Junchao Zhang
>
>
> On Mon, Sep 23, 2019 at 5:04 PM Mills, Richard Tran via petsc-dev <
> petsc-dev at mcs.anl.gov> wrote:
>
>> In MatMultAdd_SeqAIJCUSPARSE, before Junchao's changes, towards the end
>> of the function it had
>>
>> if (!yy) { /* MatMult */
>> if (!cusparsestruct->stream) {
>> ierr = WaitForGPU();CHKERRCUDA(ierr);
>> }
>> }
>>
>> I assume we don't need the logic to do this only in the MatMult() with no
>> add case and should just do this all the time, for the purposes of timing
>> if no other reason. Is there some reason to NOT do this because of worries
>> the about effects that these WaitForGPU() invocations might have on
>> performance?
>>
>> I notice other problems in aijcusparse.cu, now that I look closer. In
>> MatMultTransposeAdd_SeqAIJCUSPARSE(), I see that we have GPU timing calls
>> around the cusparse_csr_spmv() (but no WaitForGPU() inside the timed
>> region). I believe this is another area in which we get a meaningless
>> timing. It looks like we need a WaitForGPU() there, and then maybe inside
>> the timed region handling the scatter. (I don't know if this stuff happens
>> asynchronously or not.) But do we potentially want two WaitForGPU() calls
>> in one function, just to help with getting timings? I don't have a good
>> idea of how much overhead this adds.
>>
>> --Richard
>>
>> On 9/21/19 12:03 PM, Zhang, Junchao via petsc-dev wrote:
>>
>> I made the following changes:
>> 1) In MatMultAdd_SeqAIJCUSPARSE, use this code sequence at the end
>> ierr = WaitForGPU();CHKERRCUDA(ierr);
>> ierr = PetscLogGpuTimeEnd();CHKERRQ(ierr);
>> ierr = PetscLogGpuFlops(2.0*a->nz);CHKERRQ(ierr);
>> PetscFunctionReturn(0);
>> 2) In MatMult_MPIAIJCUSPARSE, use the following code sequence. The old
>> code swapped the first two lines. Since with
>> -log_view, MatMultAdd_SeqAIJCUSPARSE is blocking, I changed the order to
>> have better overlap.
>> ierr =
>> VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
>> ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr);
>> ierr =
>> VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
>> ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr);
>> 3) Log time directly in the test code so we can also know execution
>> time without -log_view (hence cuda synchronization). I manually calculated
>> the Total Mflop/s for these cases for easy comparison.
>>
>> <<Note the CPU versions are copied from yesterday's results>>
>>
>>
>> ------------------------------------------------------------------------------------------------------------------------
>> Event Count Time (sec) Flop
>> --- Global --- --- Stage ---- Total GPU - CpuToGpu - -
>> GpuToCpu - GPU
>> Max Ratio Max Ratio Max Ratio Mess AvgLen
>> Reduct %T %F %M %L %R %T %F %M %L %R Mflop/s Mflop/s Count Size
>> Count Size %F
>>
>> ---------------------------------------------------------------------------------------------------------------------------------------------------------------
>> 6 MPI ranks,
>> MatMult 100 1.0 1.1895e+01 1.0 9.63e+09 1.1 2.8e+03 2.2e+05
>> 0.0e+00 24 99 97 18 0 100100100100 0 4743 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecScatterBegin 100 1.0 4.9145e-02 3.0 0.00e+00 0.0 2.8e+03 2.2e+05
>> 0.0e+00 0 0 97 18 0 0 0100100 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecScatterEnd 100 1.0 2.9441e+00 133 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 3 0 0 0 0 13 0 0 0 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>>
>> 24 MPI ranks
>> MatMult 100 1.0 3.1431e+00 1.0 2.63e+09 1.2 1.9e+04 5.9e+04
>> 0.0e+00 8 99 97 25 0 100100100100 0 17948 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecScatterBegin 100 1.0 2.0583e-02 2.3 0.00e+00 0.0 1.9e+04 5.9e+04
>> 0.0e+00 0 0 97 25 0 0 0100100 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecScatterEnd 100 1.0 1.0639e+0050.0 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 2 0 0 0 0 19 0 0 0 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>>
>> 42 MPI ranks
>> MatMult 100 1.0 2.0519e+00 1.0 1.52e+09 1.3 3.5e+04 4.1e+04
>> 0.0e+00 23 99 97 30 0 100100100100 0 27493 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecScatterBegin 100 1.0 2.0971e-02 3.4 0.00e+00 0.0 3.5e+04 4.1e+04
>> 0.0e+00 0 0 97 30 0 1 0100100 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecScatterEnd 100 1.0 8.5184e-0162.0 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 6 0 0 0 0 24 0 0 0 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>>
>> 6 MPI ranks + 6 GPUs + regular SF + log_view
>> MatMult 100 1.0 1.6863e-01 1.0 9.66e+09 1.1 2.8e+03 2.2e+05
>> 0.0e+00 0 99 97 18 0 100100100100 0 335743 629278 100 1.02e+02 100
>> 2.69e+02 100
>> VecScatterBegin 100 1.0 5.0157e-02 1.6 0.00e+00 0.0 2.8e+03 2.2e+05
>> 0.0e+00 0 0 97 18 0 24 0100100 0 0 0 0 0.00e+00 100
>> 2.69e+02 0
>> VecScatterEnd 100 1.0 4.9155e-02 2.5 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 0 0 0 0 0 20 0 0 0 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecCUDACopyTo 100 1.0 9.5078e-03 2.0 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 0 0 0 0 0 4 0 0 0 0 0 0 100 1.02e+02 0
>> 0.00e+00 0
>> VecCopyFromSome 100 1.0 2.8485e-02 1.4 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 0 0 0 0 0 14 0 0 0 0 0 0 0 0.00e+00 100
>> 2.69e+02 0
>>
>> 6 MPI ranks + 6 GPUs + regular SF + No log_view
>> MatMult: 100 1.0 1.4180e-01
>> 399268
>>
>> 6 MPI ranks + 6 GPUs + CUDA-aware SF + log_view
>> MatMult 100 1.0 1.1053e-01 1.0 9.66e+09 1.1 2.8e+03 2.2e+05
>> 0.0e+00 1 99 97 18 0 100100100100 0 512224 642075 0 0.00e+00 0
>> 0.00e+00 100
>> VecScatterBegin 100 1.0 8.3418e-03 1.5 0.00e+00 0.0 2.8e+03 2.2e+05
>> 0.0e+00 0 0 97 18 0 6 0100100 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecScatterEnd 100 1.0 2.2619e-02 1.6 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 0 0 0 0 0 16 0 0 0 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>>
>> 6 MPI ranks + 6 GPUs + CUDA-aware SF + No log_view
>> MatMult: 100 1.0 9.8344e-02
>> 575717
>>
>> 24 MPI ranks + 6 GPUs + regular SF + log_view
>> MatMult 100 1.0 1.1572e-01 1.0 2.63e+09 1.2 1.9e+04 5.9e+04
>> 0.0e+00 0 99 97 25 0 100100100100 0 489223 708601 100 4.61e+01 100
>> 6.72e+01 100
>> VecScatterBegin 100 1.0 2.0641e-02 2.0 0.00e+00 0.0 1.9e+04 5.9e+04
>> 0.0e+00 0 0 97 25 0 13 0100100 0 0 0 0 0.00e+00 100
>> 6.72e+01 0
>> VecScatterEnd 100 1.0 6.8114e-02 5.6 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 0 0 0 0 0 38 0 0 0 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecCUDACopyTo 100 1.0 6.6646e-03 2.5 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 0 0 0 0 0 3 0 0 0 0 0 0 100 4.61e+01 0
>> 0.00e+00 0
>> VecCopyFromSome 100 1.0 1.0546e-02 1.7 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 0 0 0 0 0 7 0 0 0 0 0 0 0 0.00e+00 100
>> 6.72e+01 0
>>
>> 24 MPI ranks + 6 GPUs + regular SF + No log_view
>> MatMult: 100 1.0 9.8254e-02
>> 576201
>>
>> 24 MPI ranks + 6 GPUs + CUDA-aware SF + log_view
>> MatMult 100 1.0 1.1602e-01 1.0 2.63e+09 1.2 1.9e+04 5.9e+04
>> 0.0e+00 1 99 97 25 0 100100100100 0 487956 707524 0 0.00e+00 0
>> 0.00e+00 100
>> VecScatterBegin 100 1.0 2.7088e-02 7.0 0.00e+00 0.0 1.9e+04 5.9e+04
>> 0.0e+00 0 0 97 25 0 8 0100100 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>> VecScatterEnd 100 1.0 8.4262e-02 3.0 0.00e+00 0.0 0.0e+00 0.0e+00
>> 0.0e+00 1 0 0 0 0 52 0 0 0 0 0 0 0 0.00e+00 0
>> 0.00e+00 0
>>
>> 24 MPI ranks + 6 GPUs + CUDA-aware SF + No log_view
>> MatMult: 100 1.0 1.0397e-01
>> 544510
>>
>>
>>
>>
>>
>>
>>
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