What is nfft1, nfft2, and nfft3 for this system?
On Thu, Oct 9, 2014 at 8:20 AM, Pablo Ródenas <pablo.rodenas.bsc.es> wrote:
> Dear Scott,
>
> you are right, this is a messy change.
> We only saw clear to change from 65536 to 65535.
> But after this change on the kPMEFillChargeGridBuffer function, we got
> the error on the kPMEReduceChargeGridBuffer one. We saw that the value
> of block variable on the kPMEReduceChargeGridBuffer function is 66150,
> greater than the one of our card, so we try to solve it with a quick
> change in order to adapt it to our card maximum values. Please, could
> you try to fix this function too?
>
> FYI, the maximum values of our card are:
> Maximum number of threads per block: 1024
> Maximum sizes of each dimension of a block: 1024 x 1024 x 64
> Maximum sizes of each dimension of a grid: 65535 x 65535 x 65535
>
> Thank you very much for your answers!
>
> Best regards,
> Pablo.
>
>
> El 09/10/14 a las #4, Scott Le Grand escribió:
> > Also do *not* *mess* *with* LOADSIZE. You will wake the CUDAThuhlu with
> > such actions and no one wants that...
> >
> > The only change you should make here is changing 65536 to 65535.
> >
> > That said, thanks for hitting this corner case! Fix shortly...
> >
> > On Thu, Oct 9, 2014 at 8:06 AM, Scott Le Grand <varelse2005.gmail.com>
> > wrote:
> >
> >> Looking closer at this thread, could you try using 65,535 instead of
> >> 65,536?
> >>
> >> http://en.wikipedia.org/wiki/CUDA, specifically maximum x dimension on
> SM
> >> 2.0 GPUs is 65,535...
> >>
> >> Missed it by one... Works fine on any Kepler or better class GPU
> because
> >> this limit was raised to 2^31 - 1
> >>
> >> Ironically, y and z are still limited to 65,535. I'll check in a fix
> >> shortly...
> >>
> >>
> >>
> >> On Thu, Oct 9, 2014 at 7:58 AM, Scott Le Grand <varelse2005.gmail.com>
> >> wrote:
> >>
> >>> Broken.
> >>>
> >>> Do not use this.
> >>>
> >>> The threadblocks *have* to be 64 for this to work (4 x 4 x 4
> >>> interpolation)...
> >>>
> >>>
> >>>
> >>>
> >>> On Thu, Oct 9, 2014 at 7:22 AM, Pablo Ródenas <pablo.rodenas.bsc.es>
> >>> wrote:
> >>>
> >>>> Dear Jason and everybody,
> >>>>
> >>>> finally I found that this Amber bug comes from the file
> >>>> $AMBERHOME/src/pmemd/src/cuda/kPMEInterpolation.cu.
> >>>>
> >>>> There is the following hardcoded value (instead of getting it by
> asking
> >>>> to the card) in the function kPMEFillChargeGridBuffer which I replaced
> >>>> by the settings of my card (Tesla M2090):
> >>>> + (line ~400)
> >>>> int lblocks = min(blocks,
> 65535);
> >>>> kPMEFillChargeGridBuffer_kernel<<<lblocks, 64>>>(offset);
> >>>> LAUNCHERROR("kPMEFillChargeGridBuffer");
> >>>> offset += 65535;
> >>>> blocks -= 65535;
> >>>> -
> >>>> int lblocks = min(blocks,
> 65536);
> >>>> kPMEFillChargeGridBuffer_kernel<<<lblocks, 64>>>(offset);
> >>>> LAUNCHERROR("kPMEFillChargeGridBuffer");
> >>>> offset += 65536;
> >>>> blocks -= 65536;
> >>>>
> >>>>
> >>>> After this change, Amber continues its execution until the next error:
> >>>> kPMEReduceChargeGridBuffer. I have also solved this error by modifying
> >>>> the function kPMEReduceChargeGridBuffer and its cuda kernel function
> >>>> kPMEReduceChargeGridBuffer_kernel. So my changes are:
> >>>> + (line ~166)
> >>>> kPMEReduceChargeGridBuffer_kernel(int offset)
> >>>> {
> >>>> unsigned int pos = blockIdx.x *
> >>>> blockDim.x + threadIdx.x + offset * blockDim.x;
> >>>> -
> >>>> kPMEReduceChargeGridBuffer_kernel()
> >>>> {
> >>>> unsigned int pos = blockIdx.x *
> >>>> blockDim.x + threadIdx.x;
> >>>>
> >>>> and
> >>>>
> >>>> + (line ~209)
> >>>> long long blocks = (gpu->sim.nfft1 * gpu->sim.nfft2 *
> gpu->sim.nfft3
> >>>> + 127) >> 7;
> >>>> int offset = 0;
> >>>>
> >>>> while (blocks > 0)
> >>>> {
> >>>> long long lblocks = min(blocks,
> >>>> 65535ll);
> >>>> kPMEReduceChargeGridBuffer_kernel<<<lblocks, 128>>>(offset);
> >>>> LAUNCHERROR("kPMEReduceChargeGridBuffer");
> >>>> offset += 65535;
> >>>> blocks -= 65535;
> >>>> }
> >>>> -
> >>>> unsigned int blocks = (gpu->sim.nfft1 * gpu->sim.nfft2 *
> >>>> gpu->sim.nfft3 + 127) >> 7;
> >>>> kPMEReduceChargeGridBuffer_kernel<<<blocks, 128>>>();
> >>>> LAUNCHERROR("kPMEReduceChargeGridBuffer");
> >>>>
> >>>>
> >>>> Now it seems to work and I got 0 errors in the amber cuda tests. But I
> >>>> cannot ensure that this code will produce the right values for our
> >>>> calculates, the execution is simply working.
> >>>>
> >>>> Please, can you check your pmemd.cuda code in order to get it working
> >>>> for cards with lower grid and block size? Then we will be very glad if
> >>>> you make a new update with a tested patch solving these issues.
> >>>>
> >>>> Thank you for your attention.
> >>>>
> >>>> Best regards,
> >>>> Pablo.
> >>>>
> >>>>
> >>>> El 04/09/14 a las #4, Jason Swails escribió:
> >>>>> On Thu, Sep 4, 2014 at 2:17 AM, Pablo Ródenas <pablo.rodenas.bsc.es>
> >>>> wrote:
> >>>>>> Good morning,
> >>>>>>
> >>>>>> could you reproduce the problem with the files provided?
> >>>>>>
> >>>>>>
> >>>>> O
> >>>>> n my computer (GTX 680, 2 GB of memory), I get a memory allocation
> >>>> error
> >>>>> because 2 GB is not enough for your system (ca. 700K+ atoms). When I
> >>>> move
> >>>>> to a K20c (4 GB of memory), it runs fine for over 10 minutes (after
> >>>> which I
> >>>>> killed it because your input files would have run for 10 hours on the
> >>>>> K20c). That machine has the nVidia toolkit version 5.0 and the
> 331.38
> >>>>> drivers on it.
> >>>>>
> >>>>> I'm not sure why you're having problems... Have you tried running
> the
> >>>> GPU
> >>>>> validation suite? I know Ross Walker posted a link to it on a
> previous
> >>>>> post, but I can't seem to locate it right now...
> >>>>>
> >>>>> HTH,
> >>>>> Jason
> >>>>>
> >>>> --
> >>>> Pablo Ródenas Barquero (pablo.rodenas.bsc.es)
> >>>> BSC - Centro Nacional de Supercomputación
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> >>>> e-mail: support.bsc.es Fax: +34-93-413 77 21
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> --
> Pablo Ródenas Barquero (pablo.rodenas.bsc.es)
> BSC - Centro Nacional de Supercomputación
> C/ Jordi Girona, 31 WWW: http://www.bsc.es
> 08034 Barcelona, Spain Tel: +34-93-405 42 29
> e-mail: support.bsc.es Fax: +34-93-413 77 21
> -----------------------------------------------
> CNAG - Centre Nacional Anàlisi Genòmica
> C/ Baldiri Reixac, 4 WWW: http://www.cnag.cat
> 08028 Barcelona, Spain Tel: +34-93-403 37 54
> e-mail: cnag_support.bsc.es
> -----------------------------------------------
>
>
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> individual or entity to which it is addressed and may contain
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Received on Thu Oct 09 2014 - 08:30:04 PDT