[petsc-dev] MatPinToCPU
Smith, Barry F.
bsmith at mcs.anl.gov
Mon Jul 29 16:31:06 CDT 2019
I don't understand the notation in the legend on the second page
12,288 cpus and no GPUs ?
24 GPUs? or 6 GPUs
192 GPUs?
1536 GPUs?
12,288 GPUs? or 12288/4 = 3072 GPUs?
So on the largest run using GPUs or not takes pretty much exactly the same
amount of time?
What about 6 GPUs vs 24 CPUs ? Same equal amount of time.
Can you send some log summaries
> On Jul 29, 2019, at 4:01 PM, Mark Adams <mfadams at lbl.gov> wrote:
>
> FYI, CUDA is running and here is some preliminary data on up to 1/8 of SUMMIT. This run with 4 cores/processes per GPU, so the GPU is virtualized into 4 GPUs.
>
> On Sun, Jul 28, 2019 at 2:34 PM Karl Rupp <rupp at iue.tuwien.ac.at> wrote:
> Hi Mark,
>
> feel free to submit a fresh pull request now. I looked at your latest
> commit in the repository in order to cherry-pick it, but it looked like
> it had a few other bits in it as well.
>
> Best regards,
> Karli
>
>
> On 7/28/19 6:27 PM, Mark Adams via petsc-dev wrote:
> > This is looking good. I'm not seeing the numerical problems, but I've
> > just hid them by avoiding the GPU on coarse grids.
> >
> > Should I submit a pull request now or test more or wait for Karl?
> >
> > On Sat, Jul 27, 2019 at 7:37 PM Mark Adams <mfadams at lbl.gov
> > <mailto:mfadams at lbl.gov>> wrote:
> >
> > Barry, I fixed CUDA to pin to CPUs correctly for GAMG at least.
> > There are some hacks here that we can work on.
> >
> > I will start testing it tomorrow, but I am pretty sure that I have
> > not regressed. I am hoping that this will fix the numerical
> > problems, which seem to be associated with empty processors.
> >
> > I did need to touch code outside of GAMG and CUDA. It might be nice
> > to test this in a next.
> >
> > GAMG now puts all reduced processorg grids on the CPU. This could be
> > looked at in the future.
> >
> >
> > On Sat, Jul 27, 2019 at 1:00 PM Smith, Barry F. <bsmith at mcs.anl.gov
> > <mailto:bsmith at mcs.anl.gov>> wrote:
> >
> >
> >
> > > On Jul 27, 2019, at 11:53 AM, Mark Adams <mfadams at lbl.gov
> > <mailto:mfadams at lbl.gov>> wrote:
> > >
> > >
> > > On Sat, Jul 27, 2019 at 11:39 AM Smith, Barry F.
> > <bsmith at mcs.anl.gov <mailto:bsmith at mcs.anl.gov>> wrote:
> > >
> > > Good catch. Thanks. Maybe the SeqCUDA has the same problem?
> > >
> > > THis is done (I may have done it).
> > >
> > > Now it seems to me that when you call VecPinToCPU you are
> > setting up and don't have data, so this copy does not seem
> > necessary. Maybe remove the copy here:
> > >
> > > PetscErrorCode VecPinToCPU_MPICUDA(Vec V,PetscBool pin)
> > > {
> > > PetscErrorCode ierr;
> > >
> > > PetscFunctionBegin;
> > > V->pinnedtocpu = pin;
> > > if (pin) {
> > > ierr = VecCUDACopyFromGPU(V);CHKERRQ(ierr); ????
> >
> > The copy from GPU should actually only do anything if the
> > GPU already has data and PETSC_OFFLOAD_GPU. If the GPU does not
> > have data
> > the copy doesn't do anything. When one calls VecPinToCPU() one
> > doesn't know where the data is so the call must be made, but it
> > may do nothing
> >
> > Note that VecCUDACopyFromGPU() calls
> > VecCUDAAllocateCheckHost() not VecCUDAAllocateCheck() so the GPU
> > will not allocate space,
> > VecCUDAAllocateCheck() is called from VecCUDACopyToGPU().
> >
> > Yes, perhaps the naming could be more consistent:
> >
> > 1) in one place it is Host in an other place it is nothing
> > 2) some places it is Host, Device, some places GPU,CPU
> >
> > Perhaps Karl can make these all consistent and simpler in
> > his refactorization
> >
> >
> > Barry
> >
> >
> > >
> > > or
> > >
> > > Not allocate the GPU if it is pinned by added in a check here:
> > >
> > > PetscErrorCode VecCUDAAllocateCheck(Vec v)
> > > {
> > > PetscErrorCode ierr;
> > > cudaError_t err;
> > > cudaStream_t stream;
> > > Vec_CUDA *veccuda;
> > >
> > > PetscFunctionBegin;
> > > if (!v->spptr) {
> > > ierr = PetscMalloc(sizeof(Vec_CUDA),&v->spptr);CHKERRQ(ierr);
> > > veccuda = (Vec_CUDA*)v->spptr;
> > > if (v->valid_GPU_array != PETSC_OFFLOAD_CPU) {
> > > err =
> > cudaMalloc((void**)&veccuda->GPUarray_allocated,sizeof(PetscScalar)*((PetscBLASInt)v->map->n));CHKERRCUDA(err);
> > > veccuda->GPUarray = veccuda->GPUarray_allocated;
> > > err = cudaStreamCreate(&stream);CHKERRCUDA(err);
> > > veccuda->stream = stream;
> > > veccuda->hostDataRegisteredAsPageLocked = PETSC_FALSE;
> > > if (v->valid_GPU_array == PETSC_OFFLOAD_UNALLOCATED) {
> > > if (v->data && ((Vec_Seq*)v->data)->array) {
> > > v->valid_GPU_array = PETSC_OFFLOAD_CPU;
> > > } else {
> > > v->valid_GPU_array = PETSC_OFFLOAD_GPU;
> > > }
> > > }
> > > }
> > > }
> > > PetscFunctionReturn(0);
> > > }
> > >
> > >
> > >
> > >
> > >
> > > > On Jul 27, 2019, at 10:40 AM, Mark Adams <mfadams at lbl.gov
> > <mailto:mfadams at lbl.gov>> wrote:
> > > >
> > > > Yea, I just figured out the problem. VecDuplicate_MPICUDA
> > did not call PinToCPU or even copy pinnedtocpu. It just copied
> > ops, so I added and am testing:
> > > >
> > > > ierr =
> > VecCreate_MPICUDA_Private(*v,PETSC_TRUE,w->nghost,0);CHKERRQ(ierr);
> > > > vw = (Vec_MPI*)(*v)->data;
> > > > ierr = PetscMemcpy((*v)->ops,win->ops,sizeof(struct
> > _VecOps));CHKERRQ(ierr);
> > > > ierr = VecPinToCPU(*v,win->pinnedtocpu);CHKERRQ(ierr);
> > > >
> > > > Thanks,
> > > >
> > > > On Sat, Jul 27, 2019 at 11:33 AM Smith, Barry F.
> > <bsmith at mcs.anl.gov <mailto:bsmith at mcs.anl.gov>> wrote:
> > > >
> > > > I don't understand the context. Once a vector is pinned
> > to the CPU the flag should be PETSC_OFFLOAD_CPU permanently
> > until the pin to cpu is turned off. Do you have a pinned vector
> > that has the value PETSC_OFFLOAD_GPU? For example here it is
> > set to PETSC_OFFLOAD_CPU
> > > >
> > > > PetscErrorCode VecPinToCPU_MPICUDA(Vec V,PetscBool pin)
> > > > {
> > > > ....
> > > > if (pin) {
> > > > ierr = VecCUDACopyFromGPU(V);CHKERRQ(ierr);
> > > > V->valid_GPU_array = PETSC_OFFLOAD_CPU; /* since the
> > CPU code will likely change values in the vector */
> > > >
> > > >
> > > > Is there any way to reproduce the problem?
> > > >
> > > > Barry
> > > >
> > > >
> > > >
> > > >
> > > > > On Jul 27, 2019, at 10:28 AM, Mark Adams <mfadams at lbl.gov
> > <mailto:mfadams at lbl.gov>> wrote:
> > > > >
> > > > > I'm not sure what to do here. The problem is that
> > pinned-to-cpu vectors are calling VecCUDACopyFromGPU here.
> > > > >
> > > > > Should I set x->valid_GPU_array to something else, like
> > PETSC_OFFLOAD_CPU, in PinToCPU so this block of code i s not
> > executed?
> > > > >
> > > > > PetscErrorCode VecGetArray(Vec x,PetscScalar **a)
> > > > > {
> > > > > PetscErrorCode ierr;
> > > > > #if defined(PETSC_HAVE_VIENNACL)
> > > > > PetscBool is_viennacltype = PETSC_FALSE;
> > > > > #endif
> > > > >
> > > > > PetscFunctionBegin;
> > > > > PetscValidHeaderSpecific(x,VEC_CLASSID,1);
> > > > > ierr = VecSetErrorIfLocked(x,1);CHKERRQ(ierr);
> > > > > if (x->petscnative) {
> > > > > #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
> > > > > if (x->valid_GPU_array == PETSC_OFFLOAD_GPU) {
> > > > > #if defined(PETSC_HAVE_VIENNACL)
> > > > > ierr =
> > PetscObjectTypeCompareAny((PetscObject)x,&is_viennacltype,VECSEQVIENNACL,VECMPIVIENNACL,VECVIENNACL,"");CHKERRQ(ierr);
> > > > > if (is_viennacltype) {
> > > > > ierr = VecViennaCLCopyFromGPU(x);CHKERRQ(ierr);
> > > > > } else
> > > > > #endif
> > > > > {
> > > > > #if defined(PETSC_HAVE_CUDA)
> > > > > ierr = VecCUDACopyFromGPU(x);CHKERRQ(ierr);
> > > > > #endif
> > > > > }
> > > > > } else if (x->valid_GPU_array ==
> > PETSC_OFFLOAD_UNALLOCATED) {
> > > > > #if defined(PETSC_HAVE_VIENNACL)
> > > > > ierr =
> > PetscObjectTypeCompareAny((PetscObject)x,&is_viennacltype,VECSEQVIENNACL,VECMPIVIENNACL,VECVIENNACL,"");CHKERRQ(ierr);
> > > > > if (is_viennacltype) {
> > > > > ierr = VecViennaCLAllocateCheckHost(x);CHKERRQ(ierr);
> > > > > } else
> > > > > #endif
> > > > > {
> > > > > #if defined(PETSC_HAVE_CUDA)
> > > > > ierr = VecCUDAAllocateCheckHost(x);CHKERRQ(ierr);
> > > > > #endif
> > > > > }
> > > > > }
> > > > > #endif
> > > > > *a = *((PetscScalar**)x->data);
> > > > > } else {
> > > > >
> > > > >
> > > > > On Tue, Jul 23, 2019 at 9:18 PM Smith, Barry F.
> > <bsmith at mcs.anl.gov <mailto:bsmith at mcs.anl.gov>> wrote:
> > > > >
> > > > > Yes, it needs to be able to switch back and forth
> > between the CPU and GPU methods so you need to move into it the
> > setting of the methods that is currently directly in the create
> > method. See how MatConvert_SeqAIJ_SeqAIJViennaCL() calls ierr =
> > MatPinToCPU_SeqAIJViennaCL(A,PETSC_FALSE);CHKERRQ(ierr); to set
> > the methods for the GPU initially.
> > > > >
> > > > > Barry
> > > > >
> > > > >
> > > > > > On Jul 23, 2019, at 7:32 PM, Mark Adams
> > <mfadams at lbl.gov <mailto:mfadams at lbl.gov>> wrote:
> > > > > >
> > > > > >
> > > > > > What are the symptoms of it not working? Does it
> > appear to be still copying the matrices to the GPU? then running
> > the functions on the GPU?
> > > > > >
> > > > > >
> > > > > > The object is dispatching the CUDA mat-vec etc.
> > > > > >
> > > > > > I suspect the pinning is incompletely done for CUDA
> > (and MPIOpenCL) matrices.
> > > > > >
> > > > > >
> > > > > > Yes, git grep MatPinToCPU shows stuff for ViennaCL but
> > not CUDA.
> > > > > >
> > > > > > I guess I can add something like this below. Do we need
> > to set the device methods? They are already set when this method
> > is set, right?
> > > > > >
> > > > > > We need the equivalent of
> > > > > >
> > > > > > static PetscErrorCode MatPinToCPU_SeqAIJViennaCL(Mat
> > A,PetscBool flg)
> > > > > > {
> > > > > > PetscFunctionBegin;
> > > > > > A->pinnedtocpu = flg;
> > > > > > if (flg) {
> > > > > > A->ops->mult = MatMult_SeqAIJ;
> > > > > > A->ops->multadd = MatMultAdd_SeqAIJ;
> > > > > > A->ops->assemblyend = MatAssemblyEnd_SeqAIJ;
> > > > > > A->ops->duplicate = MatDuplicate_SeqAIJ;
> > > > > > } else {
> > > > > > A->ops->mult = MatMult_SeqAIJViennaCL;
> > > > > > A->ops->multadd = MatMultAdd_SeqAIJViennaCL;
> > > > > > A->ops->assemblyend = MatAssemblyEnd_SeqAIJViennaCL;
> > > > > > A->ops->destroy = MatDestroy_SeqAIJViennaCL;
> > > > > > A->ops->duplicate = MatDuplicate_SeqAIJViennaCL;
> > > > > > }
> > > > > > PetscFunctionReturn(0);
> > > > > > }
> > > > > >
> > > > > > for MPIViennaCL and MPISeqAIJ Cusparse but it doesn't
> > look like it has been written yet.
> > > > > >
> > > > > >
> > > > > > >
> > > > > > > It does not seem to work. It does not look like CUDA
> > has an MatCreateVecs. Should I add one and copy this flag over?
> > > > > >
> > > > > > We do need this function. But I don't see how it
> > relates to pinning. When the matrix is pinned to the CPU we want
> > it to create CPU vectors which I assume it does.
> > > > > >
> > > > > >
> > > > > > >
> > > > > > > Mark
> > > > > >
> > > > >
> > > >
> > >
> >
> <strong_su.png><dynamic_range_log.png>
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