[petsc-users] Cannot eagerly initialize cuda, as doing so results in cuda error 35 (cudaErrorInsufficientDriver) : CUDA driver version is insufficient for CUDA runtime version
Fande Kong
fdkong.jd at gmail.com
Mon Jan 31 10:49:56 CST 2022
Sorry for the confusion. I thought I explained pretty well :-)
Good:
PETSc was linked to /usr/lib64/libcuda for libcuda
Bad:
PETSc was linked
to /apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64/stubs
for libcuda
My question would be: where should I look for libcuda?
Our HPC admin told me that I should use the one from /usr/lib64/libcuda
I am trying to understand why we need to link to "stubs"?
Just to be clear, I am fine with PETSc-main as is since I can use a compute
node to compile PETSc. However, here I am trying really hard to
understand where I should look for the right libcuda.
Thanks for your help
Fande
On Mon, Jan 31, 2022 at 9:19 AM Junchao Zhang <junchao.zhang at gmail.com>
wrote:
> Fande,
> From your configure_main.log
>
> cuda:
> Version: 10.1
> Includes:
> -I/apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/include
> Library:
> -Wl,-rpath,/apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64
> -L/apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64
> -L/apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64/stubs
> -lcudart -lcufft -lcublas -lcusparse -lcusolver -lcurand -lcuda
>
>
> You can see the `stubs` directory is not in rpath. We took a lot of
> effort to achieve that. You need to double check the reason.
>
> --Junchao Zhang
>
>
> On Mon, Jan 31, 2022 at 9:40 AM Fande Kong <fdkong.jd at gmail.com> wrote:
>
>> OK,
>>
>> Finally we resolved the issue. The issue was that there were two libcuda
>> libs on a GPU compute node: /usr/lib64/libcuda
>> and /apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64/stubs/libcuda.
>> But on a login node there is one libcuda lib:
>> /apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64/stubs/libcuda.
>> We can not see /usr/lib64/libcuda from a login node where I was compiling
>> the code.
>>
>> Before the Junchao's commit, we did not have "-Wl,-rpath" to force PETSc
>> take
>> /apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64/stubs/libcuda.
>> A code compiled on a login node could correctly pick up the cuda lib
>> from /usr/lib64/libcuda at runtime. When with "-Wl,-rpath", the code
>> always takes the cuda lib from
>> /apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64/stubs/libcuda,
>> wihch was a bad lib.
>>
>> Right now, I just compiled code on a compute node instead of a login
>> node, PETSc was able to pick up the correct lib from /usr/lib64/libcuda,
>> and everything ran fine.
>>
>> I am not sure whether or not it is a good idea to search for "stubs"
>> since the system might have the correct ones in other places. Should not I
>> do a batch compiling?
>>
>> Thanks,
>>
>> Fande
>>
>>
>> On Wed, Jan 26, 2022 at 1:49 PM Fande Kong <fdkong.jd at gmail.com> wrote:
>>
>>> Yes, please see the attached file.
>>>
>>> Fande
>>>
>>> On Wed, Jan 26, 2022 at 11:49 AM Junchao Zhang <junchao.zhang at gmail.com>
>>> wrote:
>>>
>>>> Do you have the configure.log with main?
>>>>
>>>> --Junchao Zhang
>>>>
>>>>
>>>> On Wed, Jan 26, 2022 at 12:26 PM Fande Kong <fdkong.jd at gmail.com>
>>>> wrote:
>>>>
>>>>> I am on the petsc-main
>>>>>
>>>>> commit 1390d3a27d88add7d79c9b38bf1a895ae5e67af6
>>>>>
>>>>> Merge: 96c919c d5f3255
>>>>>
>>>>> Author: Satish Balay <balay at mcs.anl.gov>
>>>>>
>>>>> Date: Wed Jan 26 10:28:32 2022 -0600
>>>>>
>>>>>
>>>>> Merge remote-tracking branch 'origin/release'
>>>>>
>>>>>
>>>>> It is still broken.
>>>>>
>>>>> Thanks,
>>>>>
>>>>>
>>>>> Fande
>>>>>
>>>>> On Wed, Jan 26, 2022 at 7:40 AM Junchao Zhang <junchao.zhang at gmail.com>
>>>>> wrote:
>>>>>
>>>>>> The good uses the compiler's default library/header path. The bad
>>>>>> searches from cuda toolkit path and uses rpath linking.
>>>>>> Though the paths look the same on the login node, they could have
>>>>>> different behavior on a compute node depending on its environment.
>>>>>> I think we fixed the issue in cuda.py (i.e., first try the compiler's
>>>>>> default, then toolkit). That's why I wanted Fande to use petsc/main.
>>>>>>
>>>>>> --Junchao Zhang
>>>>>>
>>>>>>
>>>>>> On Tue, Jan 25, 2022 at 11:59 PM Barry Smith <bsmith at petsc.dev>
>>>>>> wrote:
>>>>>>
>>>>>>>
>>>>>>> bad has extra
>>>>>>>
>>>>>>> -L/apps/local/spack/software/gcc-7.5.0/cuda-10.1.243-v4ymjqcrr7f72qfiuzsstuy5jiajbuey/lib64/stubs
>>>>>>> -lcuda
>>>>>>>
>>>>>>> good does not.
>>>>>>>
>>>>>>> Try removing the stubs directory and -lcuda from the bad
>>>>>>> $PETSC_ARCH/lib/petsc/conf/variables and likely the bad will start working.
>>>>>>>
>>>>>>> Barry
>>>>>>>
>>>>>>> I never liked the stubs stuff.
>>>>>>>
>>>>>>> On Jan 25, 2022, at 11:29 PM, Fande Kong <fdkong.jd at gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>> Hi Junchao,
>>>>>>>
>>>>>>> I attached a "bad" configure log and a "good" configure log.
>>>>>>>
>>>>>>> The "bad" one was on produced
>>>>>>> at 246ba74192519a5f34fb6e227d1c64364e19ce2c
>>>>>>>
>>>>>>> and the "good" one at 384645a00975869a1aacbd3169de62ba40cad683
>>>>>>>
>>>>>>> This good hash is the last good hash that is just the right before
>>>>>>> the bad one.
>>>>>>>
>>>>>>> I think you could do a comparison between these two logs, and check
>>>>>>> what the differences were.
>>>>>>>
>>>>>>> Thanks,
>>>>>>>
>>>>>>> Fande
>>>>>>>
>>>>>>> On Tue, Jan 25, 2022 at 8:21 PM Junchao Zhang <
>>>>>>> junchao.zhang at gmail.com> wrote:
>>>>>>>
>>>>>>>> Fande, could you send the configure.log that works (i.e., before
>>>>>>>> this offending commit)?
>>>>>>>> --Junchao Zhang
>>>>>>>>
>>>>>>>>
>>>>>>>> On Tue, Jan 25, 2022 at 8:21 PM Fande Kong <fdkong.jd at gmail.com>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>> Not sure if this is helpful. I did "git bisect", and here was the
>>>>>>>>> result:
>>>>>>>>>
>>>>>>>>> [kongf at sawtooth2 petsc]$ git bisect bad
>>>>>>>>> 246ba74192519a5f34fb6e227d1c64364e19ce2c is the first bad commit
>>>>>>>>> commit 246ba74192519a5f34fb6e227d1c64364e19ce2c
>>>>>>>>> Author: Junchao Zhang <jczhang at mcs.anl.gov>
>>>>>>>>> Date: Wed Oct 13 05:32:43 2021 +0000
>>>>>>>>>
>>>>>>>>> Config: fix CUDA library and header dirs
>>>>>>>>>
>>>>>>>>> :040000 040000 187c86055adb80f53c1d0565a8888704fec43a96
>>>>>>>>> ea1efd7f594fd5e8df54170bc1bc7b00f35e4d5f M config
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> Started from this commit, and GPU did not work for me on our HPC
>>>>>>>>>
>>>>>>>>> Thanks,
>>>>>>>>> Fande
>>>>>>>>>
>>>>>>>>> On Tue, Jan 25, 2022 at 7:18 PM Fande Kong <fdkong.jd at gmail.com>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Tue, Jan 25, 2022 at 9:04 AM Jacob Faibussowitsch <
>>>>>>>>>> jacob.fai at gmail.com> wrote:
>>>>>>>>>>
>>>>>>>>>>> Configure should not have an impact here I think. The reason I
>>>>>>>>>>> had you run `cudaGetDeviceCount()` is because this is the CUDA call (and in
>>>>>>>>>>> fact the only CUDA call) in the initialization sequence that returns the
>>>>>>>>>>> error code. There should be no prior CUDA calls. Maybe this is a problem
>>>>>>>>>>> with oversubscribing GPU’s? In the runs that crash, how many ranks are
>>>>>>>>>>> using any given GPU at once? Maybe MPS is required.
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> I used one MPI rank.
>>>>>>>>>>
>>>>>>>>>> Fande
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Best regards,
>>>>>>>>>>>
>>>>>>>>>>> Jacob Faibussowitsch
>>>>>>>>>>> (Jacob Fai - booss - oh - vitch)
>>>>>>>>>>>
>>>>>>>>>>> On Jan 21, 2022, at 12:01, Fande Kong <fdkong.jd at gmail.com>
>>>>>>>>>>> wrote:
>>>>>>>>>>>
>>>>>>>>>>> Thanks Jacob,
>>>>>>>>>>>
>>>>>>>>>>> On Thu, Jan 20, 2022 at 6:25 PM Jacob Faibussowitsch <
>>>>>>>>>>> jacob.fai at gmail.com> wrote:
>>>>>>>>>>>
>>>>>>>>>>>> Segfault is caused by the following check at
>>>>>>>>>>>> src/sys/objects/device/impls/cupm/cupmdevice.cxx:349 being a
>>>>>>>>>>>> PetscUnlikelyDebug() rather than just PetscUnlikely():
>>>>>>>>>>>>
>>>>>>>>>>>> ```
>>>>>>>>>>>> if (PetscUnlikelyDebug(_defaultDevice < 0)) { // _defaultDevice
>>>>>>>>>>>> is in fact < 0 here and uncaught
>>>>>>>>>>>> ```
>>>>>>>>>>>>
>>>>>>>>>>>> To clarify:
>>>>>>>>>>>>
>>>>>>>>>>>> “lazy” initialization is not that lazy after all, it still does
>>>>>>>>>>>> some 50% of the initialization that “eager” initialization does. It stops
>>>>>>>>>>>> short initializing the CUDA runtime, checking CUDA aware MPI, gathering
>>>>>>>>>>>> device data, and initializing cublas and friends. Lazy also importantly
>>>>>>>>>>>> swallows any errors that crop up during initialization, storing the
>>>>>>>>>>>> resulting error code for later (specifically _defaultDevice =
>>>>>>>>>>>> -init_error_value;).
>>>>>>>>>>>>
>>>>>>>>>>>> So whether you initialize lazily or eagerly makes no difference
>>>>>>>>>>>> here, as _defaultDevice will always contain -35.
>>>>>>>>>>>>
>>>>>>>>>>>> The bigger question is why cudaGetDeviceCount() is returning
>>>>>>>>>>>> cudaErrorInsufficientDriver. Can you compile and run
>>>>>>>>>>>>
>>>>>>>>>>>> ```
>>>>>>>>>>>> #include <cuda_runtime.h>
>>>>>>>>>>>>
>>>>>>>>>>>> int main()
>>>>>>>>>>>> {
>>>>>>>>>>>> int ndev;
>>>>>>>>>>>> return cudaGetDeviceCount(&ndev):
>>>>>>>>>>>> }
>>>>>>>>>>>> ```
>>>>>>>>>>>>
>>>>>>>>>>>> Then show the value of "echo $?”?
>>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Modify your code a little to get more information.
>>>>>>>>>>>
>>>>>>>>>>> #include <cuda_runtime.h>
>>>>>>>>>>> #include <cstdio>
>>>>>>>>>>>
>>>>>>>>>>> int main()
>>>>>>>>>>> {
>>>>>>>>>>> int ndev;
>>>>>>>>>>> int error = cudaGetDeviceCount(&ndev);
>>>>>>>>>>> printf("ndev %d \n", ndev);
>>>>>>>>>>> printf("error %d \n", error);
>>>>>>>>>>> return 0;
>>>>>>>>>>> }
>>>>>>>>>>>
>>>>>>>>>>> Results:
>>>>>>>>>>>
>>>>>>>>>>> $ ./a.out
>>>>>>>>>>> ndev 4
>>>>>>>>>>> error 0
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> I have not read the PETSc cuda initialization code yet. If I
>>>>>>>>>>> need to guess at what was happening. I will naively think that PETSc did
>>>>>>>>>>> not get correct GPU information in the configuration because the compiler
>>>>>>>>>>> node does not have GPUs, and there was no way to get any GPU device
>>>>>>>>>>> information.
>>>>>>>>>>>
>>>>>>>>>>> During the runtime on GPU nodes, PETSc might have incorrect
>>>>>>>>>>> information grabbed during configuration and had this kind of false error
>>>>>>>>>>> message.
>>>>>>>>>>>
>>>>>>>>>>> Thanks,
>>>>>>>>>>>
>>>>>>>>>>> Fande
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> Best regards,
>>>>>>>>>>>>
>>>>>>>>>>>> Jacob Faibussowitsch
>>>>>>>>>>>> (Jacob Fai - booss - oh - vitch)
>>>>>>>>>>>>
>>>>>>>>>>>> On Jan 20, 2022, at 17:47, Matthew Knepley <knepley at gmail.com>
>>>>>>>>>>>> wrote:
>>>>>>>>>>>>
>>>>>>>>>>>> On Thu, Jan 20, 2022 at 6:44 PM Fande Kong <fdkong.jd at gmail.com>
>>>>>>>>>>>> wrote:
>>>>>>>>>>>>
>>>>>>>>>>>>> Thanks, Jed
>>>>>>>>>>>>>
>>>>>>>>>>>>> On Thu, Jan 20, 2022 at 4:34 PM Jed Brown <jed at jedbrown.org>
>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>>
>>>>>>>>>>>>>> You can't create CUDA or Kokkos Vecs if you're running on a
>>>>>>>>>>>>>> node without a GPU.
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> I am running the code on compute nodes that do have GPUs.
>>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> If you are actually running on GPUs, why would you need lazy
>>>>>>>>>>>> initialization? It would not break with GPUs present.
>>>>>>>>>>>>
>>>>>>>>>>>> Matt
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>> With PETSc-3.16.1, I got good speedup by running GAMG on
>>>>>>>>>>>>> GPUs. That might be a bug of PETSc-main.
>>>>>>>>>>>>>
>>>>>>>>>>>>> Thanks,
>>>>>>>>>>>>>
>>>>>>>>>>>>> Fande
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> KSPSetUp 13 1.0 6.4400e-01 1.0 2.02e+09 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 5 0 0 0 0 5 0 0 0 3140 64630 15
>>>>>>>>>>>>> 1.05e+02 5 3.49e+01 100
>>>>>>>>>>>>> KSPSolve 1 1.0 1.0109e+00 1.0 3.49e+10 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 87 0 0 0 0 87 0 0 0 34522 69556 4
>>>>>>>>>>>>> 4.35e-03 1 2.38e-03 100
>>>>>>>>>>>>> KSPGMRESOrthog 142 1.0 1.2674e-01 1.0 1.06e+10 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 27 0 0 0 0 27 0 0 0 83755 87801 0
>>>>>>>>>>>>> 0.00e+00 0 0.00e+00 100
>>>>>>>>>>>>> SNESSolve 1 1.0 4.4402e+01 1.0 4.00e+10 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 21100 0 0 0 21100 0 0 0 901 51365 57
>>>>>>>>>>>>> 1.10e+03 52 8.78e+02 100
>>>>>>>>>>>>> SNESSetUp 1 1.0 3.9101e-05 1.0 0.00e+00 0.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>>>>>>>>>>> 0.00e+00 0 0.00e+00 0
>>>>>>>>>>>>> SNESFunctionEval 2 1.0 1.7097e+01 1.0 1.60e+07 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 8 0 0 0 0 8 0 0 0 0 1 0 0
>>>>>>>>>>>>> 0.00e+00 6 1.92e+02 0
>>>>>>>>>>>>> SNESJacobianEval 1 1.0 1.6213e+01 1.0 2.80e+07 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 8 0 0 0 0 8 0 0 0 0 2 0 0
>>>>>>>>>>>>> 0.00e+00 1 3.20e+01 0
>>>>>>>>>>>>> SNESLineSearch 1 1.0 8.5582e+00 1.0 1.24e+08 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 4 0 0 0 0 4 0 0 0 0 14 64153 1
>>>>>>>>>>>>> 3.20e+01 3 9.61e+01 94
>>>>>>>>>>>>> PCGAMGGraph_AGG 5 1.0 3.0509e+00 1.0 8.19e+07 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 1 0 0 0 0 1 0 0 0 0 27 0 5
>>>>>>>>>>>>> 3.49e+01 9 7.43e+01 0
>>>>>>>>>>>>> PCGAMGCoarse_AGG 5 1.0 3.8711e+00 1.0 0.00e+00 0.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 2 0 0 0 0 2 0 0 0 0 0 0 0
>>>>>>>>>>>>> 0.00e+00 0 0.00e+00 0
>>>>>>>>>>>>> PCGAMGProl_AGG 5 1.0 7.0748e-01 1.0 0.00e+00 0.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>>>>>>>>>>> 0.00e+00 0 0.00e+00 0
>>>>>>>>>>>>> PCGAMGPOpt_AGG 5 1.0 1.2904e+00 1.0 2.14e+09 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 1 5 0 0 0 1 5 0 0 0 1661 29807 26
>>>>>>>>>>>>> 7.15e+02 20 2.90e+02 99
>>>>>>>>>>>>> GAMG: createProl 5 1.0 8.9489e+00 1.0 2.22e+09 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 4 6 0 0 0 4 6 0 0 0 249 29666 31
>>>>>>>>>>>>> 7.50e+02 29 3.64e+02 96
>>>>>>>>>>>>> Graph 10 1.0 3.0478e+00 1.0 8.19e+07 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 1 0 0 0 0 1 0 0 0 0 27 0 5
>>>>>>>>>>>>> 3.49e+01 9 7.43e+01 0
>>>>>>>>>>>>> MIS/Agg 5 1.0 4.1290e-01 1.0 0.00e+00 0.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>>>>>>>>>>> 0.00e+00 0 0.00e+00 0
>>>>>>>>>>>>> SA: col data 5 1.0 1.9127e-02 1.0 0.00e+00 0.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>>>>>>>>>>> 0.00e+00 0 0.00e+00 0
>>>>>>>>>>>>> SA: frmProl0 5 1.0 6.2662e-01 1.0 0.00e+00 0.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 0
>>>>>>>>>>>>> 0.00e+00 0 0.00e+00 0
>>>>>>>>>>>>> SA: smooth 5 1.0 4.9595e-01 1.0 1.21e+08 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 244 2709 15
>>>>>>>>>>>>> 1.97e+02 15 2.55e+02 90
>>>>>>>>>>>>> GAMG: partLevel 5 1.0 4.7330e-01 1.0 6.98e+08 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 2 0 0 0 0 2 0 0 0 1475 4120 5
>>>>>>>>>>>>> 1.78e+02 10 2.55e+02 100
>>>>>>>>>>>>> PCGAMG Squ l00 1 1.0 2.6027e+00 1.0 0.00e+00 0.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 1 0 0 0 0 1 0 0 0 0 0 0 0
>>>>>>>>>>>>> 0.00e+00 0 0.00e+00 0
>>>>>>>>>>>>> PCGAMG Gal l00 1 1.0 3.8406e-01 1.0 5.48e+08 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 1 0 0 0 0 1 0 0 0 1426 4270 1
>>>>>>>>>>>>> 1.48e+02 2 2.11e+02 100
>>>>>>>>>>>>> PCGAMG Opt l00 1 1.0 2.4932e-01 1.0 7.20e+07 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 289 2653 1
>>>>>>>>>>>>> 6.41e+01 1 1.13e+02 100
>>>>>>>>>>>>> PCGAMG Gal l01 1 1.0 6.6279e-02 1.0 1.09e+08 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 1645 3851 1
>>>>>>>>>>>>> 2.40e+01 2 3.64e+01 100
>>>>>>>>>>>>> PCGAMG Opt l01 1 1.0 2.9544e-02 1.0 7.15e+06 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 242 1671 1
>>>>>>>>>>>>> 4.84e+00 1 1.23e+01 100
>>>>>>>>>>>>> PCGAMG Gal l02 1 1.0 1.8874e-02 1.0 3.72e+07 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 1974 3636 1
>>>>>>>>>>>>> 5.04e+00 2 6.58e+00 100
>>>>>>>>>>>>> PCGAMG Opt l02 1 1.0 7.4353e-03 1.0 2.40e+06 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 323 1457 1
>>>>>>>>>>>>> 7.71e-01 1 2.30e+00 100
>>>>>>>>>>>>> PCGAMG Gal l03 1 1.0 2.8479e-03 1.0 4.10e+06 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 1440 2266 1
>>>>>>>>>>>>> 4.44e-01 2 5.51e-01 100
>>>>>>>>>>>>> PCGAMG Opt l03 1 1.0 8.2684e-04 1.0 2.80e+05 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 339 1667 1
>>>>>>>>>>>>> 6.72e-02 1 2.03e-01 100
>>>>>>>>>>>>> PCGAMG Gal l04 1 1.0 1.2238e-03 1.0 2.09e+05 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 170 244 1
>>>>>>>>>>>>> 2.05e-02 2 2.53e-02 100
>>>>>>>>>>>>> PCGAMG Opt l04 1 1.0 4.1008e-04 1.0 1.77e+04 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 43 165 1
>>>>>>>>>>>>> 4.49e-03 1 1.19e-02 100
>>>>>>>>>>>>> PCSetUp 2 1.0 9.9632e+00 1.0 4.95e+09 1.0
>>>>>>>>>>>>> 0.0e+00 0.0e+00 0.0e+00 5 12 0 0 0 5 12 0 0 0 496 17826 55
>>>>>>>>>>>>> 1.03e+03 45 6.54e+02 98
>>>>>>>>>>>>> PCSetUpOnBlocks 44 1.0 9.9087e-04 1.0 2.88e+03 1.0
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>> The point of lazy initialization is to make it possible to
>>>>>>>>>>>>>> run a solve that doesn't use a GPU in PETSC_ARCH that supports GPUs,
>>>>>>>>>>>>>> regardless of whether a GPU is actually present.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Fande Kong <fdkong.jd at gmail.com> writes:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> > I spoke too soon. It seems that we have trouble creating
>>>>>>>>>>>>>> cuda/kokkos vecs
>>>>>>>>>>>>>> > now. Got Segmentation fault.
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> > Thanks,
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> > Fande
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> > Program received signal SIGSEGV, Segmentation fault.
>>>>>>>>>>>>>> > 0x00002aaab5558b11 in
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> Petsc::CUPMDevice<(Petsc::CUPMDeviceType)0>::CUPMDeviceInternal::initialize
>>>>>>>>>>>>>> > (this=0x1) at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/sys/objects/device/impls/cupm/cupmdevice.cxx:54
>>>>>>>>>>>>>> > 54 PetscErrorCode
>>>>>>>>>>>>>> CUPMDevice<T>::CUPMDeviceInternal::initialize() noexcept
>>>>>>>>>>>>>> > Missing separate debuginfos, use: debuginfo-install
>>>>>>>>>>>>>> > bzip2-libs-1.0.6-13.el7.x86_64
>>>>>>>>>>>>>> elfutils-libelf-0.176-5.el7.x86_64
>>>>>>>>>>>>>> > elfutils-libs-0.176-5.el7.x86_64 glibc-2.17-325.el7_9.x86_64
>>>>>>>>>>>>>> > libX11-1.6.7-4.el7_9.x86_64 libXau-1.0.8-2.1.el7.x86_64
>>>>>>>>>>>>>> > libattr-2.4.46-13.el7.x86_64 libcap-2.22-11.el7.x86_64
>>>>>>>>>>>>>> > libibmad-5.4.0.MLNX20190423.1d917ae-0.1.49224.x86_64
>>>>>>>>>>>>>> > libibumad-43.1.1.MLNX20200211.078947f-0.1.49224.x86_64
>>>>>>>>>>>>>> > libibverbs-41mlnx1-OFED.4.9.0.0.7.49224.x86_64
>>>>>>>>>>>>>> > libmlx4-41mlnx1-OFED.4.7.3.0.3.49224.x86_64
>>>>>>>>>>>>>> > libmlx5-41mlnx1-OFED.4.9.0.1.2.49224.x86_64
>>>>>>>>>>>>>> libnl3-3.2.28-4.el7.x86_64
>>>>>>>>>>>>>> > librdmacm-41mlnx1-OFED.4.7.3.0.6.49224.x86_64
>>>>>>>>>>>>>> > librxe-41mlnx1-OFED.4.4.2.4.6.49224.x86_64
>>>>>>>>>>>>>> libxcb-1.13-1.el7.x86_64
>>>>>>>>>>>>>> > libxml2-2.9.1-6.el7_9.6.x86_64
>>>>>>>>>>>>>> numactl-libs-2.0.12-5.el7.x86_64
>>>>>>>>>>>>>> > systemd-libs-219-78.el7_9.3.x86_64
>>>>>>>>>>>>>> xz-libs-5.2.2-1.el7.x86_64
>>>>>>>>>>>>>> > zlib-1.2.7-19.el7_9.x86_64
>>>>>>>>>>>>>> > (gdb) bt
>>>>>>>>>>>>>> > #0 0x00002aaab5558b11 in
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> Petsc::CUPMDevice<(Petsc::CUPMDeviceType)0>::CUPMDeviceInternal::initialize
>>>>>>>>>>>>>> > (this=0x1) at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/sys/objects/device/impls/cupm/cupmdevice.cxx:54
>>>>>>>>>>>>>> > #1 0x00002aaab5558db7 in
>>>>>>>>>>>>>> > Petsc::CUPMDevice<(Petsc::CUPMDeviceType)0>::getDevice
>>>>>>>>>>>>>> > (this=this at entry=0x2aaab7f37b70
>>>>>>>>>>>>>> > <CUDADevice>, device=0x115da00, id=-35, id at entry=-1) at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/sys/objects/device/impls/cupm/cupmdevice.cxx:344
>>>>>>>>>>>>>> > #2 0x00002aaab55577de in PetscDeviceCreate (type=type at entry
>>>>>>>>>>>>>> =PETSC_DEVICE_CUDA,
>>>>>>>>>>>>>> > devid=devid at entry=-1, device=device at entry=0x2aaab7f37b48
>>>>>>>>>>>>>> > <defaultDevices+8>) at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/sys/objects/device/interface/device.cxx:107
>>>>>>>>>>>>>> > #3 0x00002aaab5557b3a in
>>>>>>>>>>>>>> PetscDeviceInitializeDefaultDevice_Internal
>>>>>>>>>>>>>> > (type=type at entry=PETSC_DEVICE_CUDA,
>>>>>>>>>>>>>> defaultDeviceId=defaultDeviceId at entry=-1)
>>>>>>>>>>>>>> > at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/sys/objects/device/interface/device.cxx:273
>>>>>>>>>>>>>> > #4 0x00002aaab5557bf6 in PetscDeviceInitialize
>>>>>>>>>>>>>> > (type=type at entry=PETSC_DEVICE_CUDA)
>>>>>>>>>>>>>> > at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/sys/objects/device/interface/device.cxx:234
>>>>>>>>>>>>>> > #5 0x00002aaab5661fcd in VecCreate_SeqCUDA (V=0x115d150) at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/vec/vec/impls/seq/seqcuda/veccuda.c:244
>>>>>>>>>>>>>> > #6 0x00002aaab5649b40 in VecSetType (vec=vec at entry
>>>>>>>>>>>>>> =0x115d150,
>>>>>>>>>>>>>> > method=method at entry=0x2aaab70b45b8 "seqcuda") at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/vec/vec/interface/vecreg.c:93
>>>>>>>>>>>>>> > #7 0x00002aaab579c33f in VecCreate_CUDA (v=0x115d150) at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/vec/vec/impls/mpi/mpicuda/
>>>>>>>>>>>>>> > mpicuda.cu:214
>>>>>>>>>>>>>> > #8 0x00002aaab5649b40 in VecSetType (vec=vec at entry
>>>>>>>>>>>>>> =0x115d150,
>>>>>>>>>>>>>> > method=method at entry=0x7fffffff9260 "cuda") at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/vec/vec/interface/vecreg.c:93
>>>>>>>>>>>>>> > #9 0x00002aaab5648bf1 in VecSetTypeFromOptions_Private
>>>>>>>>>>>>>> (vec=0x115d150,
>>>>>>>>>>>>>> > PetscOptionsObject=0x7fffffff9210) at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/vec/vec/interface/vector.c:1263
>>>>>>>>>>>>>> > #10 VecSetFromOptions (vec=0x115d150) at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/petsc/src/vec/vec/interface/vector.c:1297
>>>>>>>>>>>>>> > #11 0x00002aaab02ef227 in libMesh::PetscVector<double>::init
>>>>>>>>>>>>>> > (this=0x11cd1a0, n=441, n_local=441, fast=false,
>>>>>>>>>>>>>> ptype=libMesh::PARALLEL)
>>>>>>>>>>>>>> > at
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> /home/kongf/workhome/sawtooth/moosegpu/scripts/../libmesh/installed/include/libmesh/petsc_vector.h:693
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> > On Thu, Jan 20, 2022 at 1:09 PM Fande Kong <
>>>>>>>>>>>>>> fdkong.jd at gmail.com> wrote:
>>>>>>>>>>>>>> >
>>>>>>>>>>>>>> >> Thanks, Jed,
>>>>>>>>>>>>>> >>
>>>>>>>>>>>>>> >> This worked!
>>>>>>>>>>>>>> >>
>>>>>>>>>>>>>> >> Fande
>>>>>>>>>>>>>> >>
>>>>>>>>>>>>>> >> On Wed, Jan 19, 2022 at 11:03 PM Jed Brown <
>>>>>>>>>>>>>> jed at jedbrown.org> wrote:
>>>>>>>>>>>>>> >>
>>>>>>>>>>>>>> >>> Fande Kong <fdkong.jd at gmail.com> writes:
>>>>>>>>>>>>>> >>>
>>>>>>>>>>>>>> >>> > On Wed, Jan 19, 2022 at 11:39 AM Jacob Faibussowitsch <
>>>>>>>>>>>>>> >>> jacob.fai at gmail.com>
>>>>>>>>>>>>>> >>> > wrote:
>>>>>>>>>>>>>> >>> >
>>>>>>>>>>>>>> >>> >> Are you running on login nodes or compute nodes (I
>>>>>>>>>>>>>> can’t seem to tell
>>>>>>>>>>>>>> >>> from
>>>>>>>>>>>>>> >>> >> the configure.log)?
>>>>>>>>>>>>>> >>> >>
>>>>>>>>>>>>>> >>> >
>>>>>>>>>>>>>> >>> > I was compiling codes on login nodes, and running codes
>>>>>>>>>>>>>> on compute
>>>>>>>>>>>>>> >>> nodes.
>>>>>>>>>>>>>> >>> > Login nodes do not have GPUs, but compute nodes do have
>>>>>>>>>>>>>> GPUs.
>>>>>>>>>>>>>> >>> >
>>>>>>>>>>>>>> >>> > Just to be clear, the same thing (code, machine) with
>>>>>>>>>>>>>> PETSc-3.16.1
>>>>>>>>>>>>>> >>> worked
>>>>>>>>>>>>>> >>> > perfectly. I have this trouble with PETSc-main.
>>>>>>>>>>>>>> >>>
>>>>>>>>>>>>>> >>> I assume you can
>>>>>>>>>>>>>> >>>
>>>>>>>>>>>>>> >>> export PETSC_OPTIONS='-device_enable lazy'
>>>>>>>>>>>>>> >>>
>>>>>>>>>>>>>> >>> and it'll work.
>>>>>>>>>>>>>> >>>
>>>>>>>>>>>>>> >>> I think this should be the default. The main complaint is
>>>>>>>>>>>>>> that timing the
>>>>>>>>>>>>>> >>> first GPU-using event isn't accurate if it includes
>>>>>>>>>>>>>> initialization, but I
>>>>>>>>>>>>>> >>> think this is mostly hypothetical because you can't trust
>>>>>>>>>>>>>> any timing that
>>>>>>>>>>>>>> >>> doesn't preload in some form and the first GPU-using
>>>>>>>>>>>>>> event will almost
>>>>>>>>>>>>>> >>> always be something uninteresting so I think it will
>>>>>>>>>>>>>> rarely lead to
>>>>>>>>>>>>>> >>> confusion. Meanwhile, eager initialization is viscerally
>>>>>>>>>>>>>> disruptive for
>>>>>>>>>>>>>> >>> lots of people.
>>>>>>>>>>>>>> >>>
>>>>>>>>>>>>>> >>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> --
>>>>>>>>>>>> What most experimenters take for granted before they begin
>>>>>>>>>>>> their experiments is infinitely more interesting than any results to which
>>>>>>>>>>>> their experiments lead.
>>>>>>>>>>>> -- Norbert Wiener
>>>>>>>>>>>>
>>>>>>>>>>>> https://www.cse.buffalo.edu/~knepley/
>>>>>>>>>>>> <http://www.cse.buffalo.edu/~knepley/>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>> <configure_bad.log><configure_good.log>
>>>>>>>
>>>>>>>
>>>>>>>
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