[gmx-users] Using multiple GPU's

paul buscemi pbuscemi at q.com
Sat Aug 11 04:50:21 CEST 2018


Mark, Kevin,

I’ve uploaded two representative log files to Google Drive.  gms users should get the invite.

thanks
Paul

> On Aug 10, 2018, at 6:27 PM, Mark Abraham <mark.j.abraham at gmail.com> wrote:
> 
> Hi,
> 
> Kevin means you to upload the file to a file sharing service and share the
> link. Everything you've shown points to using both GPUs, but the relevant
> output about the decision is not shown.
> 
> Mark
> 
> On Sat, Aug 11, 2018, 00:58 paul buscemi <pbuscemi at q.com> wrote:
> 
>> Thanks Kevin. for the rapid response.
>> 
>> I am using 2018. I’ll check the 2018 - make sure - I was look at the
>> proper docs.   I should not note that the  GPUs are not matched.   a gtx
>> 1080ti  and a gtx 1060
>> 
>> below is some pertinent information from the log file.  ( not too sure how
>> to post a link on the user group )
>> 
>> Paul
>> 
>>> On Aug 10, 2018, at 12:31 PM, Kevin Boyd <kevin.boyd at uconn.edu> wrote:
>>> 
>>> Hi,
>>> 
>>> Can you post a link to your log file?
>>> 
>>> Also, what version of gromacs are you using? Make sure that the
>>> documentation you are following corresponds to the right version of
>>> gromacs. If you are using v 5.1 (as the link suggests), strongly consider
>>> upgrading to 2018.
>>> 
>>> Kevin
>>> 
>>> On Fri, Aug 10, 2018 at 12:57 PM, paul buscemi <pbuscemi at q.com> wrote:
>>> 
>>>> 
>>>> Dear Uses,
>>>> 
>>>> I’ve been following the examples on https://na01.safelinks.
>>>> protection.outlook.com/?url=http%3A%2F%2Fmanual.gromacs.
>>>> org%2Fdocumentation%2F5.1%2Fuser-guide%2Fmdrun-
>>>> performance.html&amp;data=02%7C01%7Ckevin.boyd%40uconn.edu%
>>>> 7Cb67f423cb92a4abac13508d5fee27522%7C17f1a87e2a254eaab9df9d439034
>>>> b080%7C0%7C1%7C636695170968044387&amp;sdata=TBSbmbdU%
>>>> 2F5kxRGsaD1IqLXzEbcJUJ6Kqg7ub%2B%2B9m6xc%3D&amp;reserved=0 for setting
>> up
>>>> multiple GP’s but have not succeeded.
>>>> Using a single GPU gmx runs well.  Nvidia and gmx see the 2 PGUs. and
>>>> I‘ve  tried   mdrun with   variations of  -gpu_id  01,    and -ntmpi,
>> but
>>>> the GPUs are not put to use.
>>>> 
>>>> Would someone suggest the proper signals to mdrun for  two GPU’s. ?
>>>> 
>>>> Running on lilnix-min sarah,  I7
>>>> 
>>>> thanks
>>>> Paul
>>>> --
>>>> 
>> 
>> GROMACS:      gmx mdrun, version 2018
>> Executable:   /usr/local/gromacs/bin//gmx
>> Data prefix:  /usr/local/gromacs
>> Working dir:  /home/rgb/Desktop/PDMS
>> Command line:
>>  gmx mdrun -deffnm pdms.sys.nvt -ntmpi 4 -ntomp 2 -gpu_id 01
>> 
>> GROMACS version:    2018
>> Precision:          single
>> Memory model:       64 bit
>> MPI library:        thread_mpi
>> OpenMP support:     enabled (GMX_OPENMP_MAX_THREADS = 64)
>> GPU support:        CUDA
>> SIMD instructions:  AVX2_256
>> FFT library:        fftw-3.3.5-fma-sse2-avx-avx2-avx2_128-avx512
>> RDTSCP usage:       enabled
>> TNG support:        enabled
>> Hwloc support:      disabled
>> Tracing support:    disabled
>> Built on:           2018-07-06 18:24:42
>> Built by:           rgb at RGB [CMAKE]
>> Build OS/arch:      Linux 4.4.0-21-generic x86_64
>> Build CPU vendor:   Intel
>> Build CPU brand:    Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz
>> Build CPU family:   6   Model: 158   Stepping: 9
>> Build CPU features: aes apic avx avx2 clfsh cmov cx8 cx16 f16c fma hle htt
>> intel lahf mmx msr nonstop_tsc pcid pclmuldq pdcm pdpe1gb popcnt pse rdrnd
>> rdtscp rtm sse2 sse3 sse4.1 sse4.2 ssse3 tdt x2apic
>> C compiler:         /usr/bin/gcc GNU 5.4.0
>> C compiler flags:    -march=core-avx2     -O3 -DNDEBUG -funroll-all-loops
>> -fexcess-precision=fast
>> C++ compiler:       /usr/bin/c++ GNU 5.4.0
>> C++ compiler flags:  -march=core-avx2    -std=c++11   -O3 -DNDEBUG
>> -funroll-all-loops -fexcess-precision=fast
>> CUDA compiler:      /usr/lib/nvidia-cuda-toolkit/bin/nvcc nvcc: NVIDIA (R)
>> Cuda compiler driver;Copyright (c) 2005-2015 NVIDIA Corporation;Built on
>> Tue_Aug_11_14:27:32_CDT_2015;Cuda compilation tools, release 7.5, V7.5.17
>> CUDA compiler
>> flags:-gencode;arch=compute_20,code=sm_20;-gencode;arch=compute_30,code=sm_30;-gencode;arch=compute_35,code=sm_35;-gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_52,code=sm_52;-gencode;arch=compute_52,code=compute_52;-use_fast_math;-D_FORCE_INLINES;;
>> ;-march=core-avx2;-std=c++11;-O3;-DNDEBUG;-funroll-all-loops;-fexcess-precision=fast;
>> CUDA driver:        9.0
>> CUDA runtime:       7.50
>> 
>> ===== latest attempt =======
>> Running on 1 node with total 4 cores, 8 logical cores, 2 compatible GPUs
>> Hardware detected:
>>  CPU info:
>>    Vendor: Intel
>>    Brand:  Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz
>>    Family: 6   Model: 158   Stepping: 9
>>    Features: aes apic avx avx2 clfsh cmov cx8 cx16 f16c fma hle htt intel
>> lahf mmx msr nonstop_tsc pcid pclmuldq pdcm pdpe1gb popcnt pse rdrnd rdtscp
>> rtm sse2 sse3 sse4.1 sse4.2 ssse3 tdt x2apic
>>  Hardware topology: Basic
>>    Sockets, cores, and logical processors:
>>      Socket  0: [   0   4] [   1   5] [   2   6] [   3   7]
>>  GPU info:
>>    Number of GPUs detected: 2
>>    #0: NVIDIA GeForce GTX 1080 Ti, compute cap.: 6.1, ECC:  no, stat:
>> compatible
>>    #1: NVIDIA GeForce GTX 1060 6GB, compute cap.: 6.1, ECC:  no, stat:
>> compatible
>> 
>> --
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