[gmx-users] g_tune_pme_mpi on GPU cluster fails

Thu Jan 8 15:51:26 CET 2015

On 08 Jan 2015, at 15:32, Ebert Maximilian <m.ebert at umontreal.ca> wrote:

> Hi Carsten,
> 
> I was benchmarking my first system and I do not see any improvement in using more than one GPU node.
Whether you see an improvement or not depends on the size of your system
and the latency of your interconnect. If it is Gigabit Ethernet, it might
be the bottleneck.

> In the end I think having a node dedicated as PME node would make sense after all since our GPU cluster only consists of 9 nodes. What do you mean with high parallelization? What do you consider high?
If you have so many cores that you end up with just a few hundred atoms per core
I would say.

Carsten

> 
> Max
> 
> -----Ursprüngliche Nachricht-----
> Von: gromacs.org_gmx-users-bounces at maillist.sys.kth.se [mailto:gromacs.org_gmx-users-bounces at maillist.sys.kth.se] Im Auftrag von Carsten Kutzner
> Gesendet: Mittwoch, 7. Januar 2015 17:04
> An: gmx-users at gromacs.org
> Betreff: Re: [gmx-users] g_tune_pme_mpi on GPU cluster fails
> 
> Hi,
> 
> there are two issues here:
> 
> a) you must not start multiple copies of g_tune_pme, but a single one.
> g_tune_pme will by itself launch MPI-parallel mdrun processes (the path to the mdrun executable needs to be specified in the MDRUN environment variable, you might need to set others as well depending on your queueing system - read g_tune_pme -h.
> 
> b) g_tune_pme can not (yet) automatically deal with GPU nodes. With GPUs, separate PME nodes will also only make sense at very high parallelization - how many of these nodes do you want to use in parallel?
> 
> Carsten
> 
> 
> On 07 Jan 2015, at 15:11, Ebert Maximilian <m.ebert at umontreal.ca> wrote:
> 
>> Hi there,
>> 
>> I have again a question regarding our GPU cluster. I tried to g_tune_pme_mpi on the cluster. After starting it across 3 nodes I get the following errors:
>> 
>> 
>> Command line:
>> g_tune_pme_mpi -v -x -deffnm 1G68_run1ns -s ../run100ns.tpr
>> 
>> Reading file ../run100ns.tpr, VERSION 5.0.1 (single precision) Reading 
>> file ../run100ns.tpr, VERSION 5.0.1 (single precision) Reading file 
>> ../run100ns.tpr, VERSION 5.0.1 (single precision) Reading file 
>> ../run100ns.tpr, VERSION 5.0.1 (single precision) Will test 1 tpr 
>> file.
>> Will test 1 tpr file.
>> Will test 1 tpr file.
>> Will test 1 tpr file.
>> [ngpu-a4-06:13382] [[25869,1],0] ORTE_ERROR_LOG: A message is 
>> attempting to be sent to a process whose contact information is 
>> unknown in file rml_oob_send.c at line 104 [ngpu-a4-06:13382] 
>> [[25869,1],0] could not get route to [[INVALID],INVALID] 
>> [ngpu-a4-06:13382] [[25869,1],0] ORTE_ERROR_LOG: A message is 
>> attempting to be sent to a process whose contact information is 
>> unknown in file base/plm_base_proxy.c at line 81 [ngpu-a4-06:13385] 
>> [[25869,1],1] ORTE_ERROR_LOG: A message is attempting to be sent to a 
>> process whose contact information is unknown in file rml_oob_send.c at 
>> line 104 [ngpu-a4-06:13385] [[25869,1],1] could not get route to [[INVALID],INVALID] [ngpu-a4-06:13385] [[25869,1],1] ORTE_ERROR_LOG: A message is attempting to be sent to a process whose contact information is unknown in file base/plm_base_proxy.c at line 81 [ngpu-a4-06:13384] [[25869,1],2] ORTE_ERROR_LOG: A message is attempting to be sent to a process whose contact information is unknown in file rml_oob_send.c at line 104 [ngpu-a4-06:13384] [[25869,1],2] could not get route to [[INVALID],INVALID] [ngpu-a4-06:13384] [[25869,1],2] ORTE_ERROR_LOG: A message is attempting to be sent to a process whose contact information is unknown in file base/plm_base_proxy.c at line 81 .....
>> =>> PBS: job killed: walltime 3641 exceeded limit 3600
>> mpirun: killing job...
>> 
>> [ngpu-a4-06:13356] [[25869,0],0]-[[25869,1],3] mca_oob_tcp_msg_recv: 
>> readv failed: Connection reset by peer (104) [ngpu-a4-06:13356] 
>> [[25869,0],0]-[[25869,1],2] mca_oob_tcp_msg_recv: readv failed: 
>> Connection reset by peer (104) [ngpu-a4-06:13356] 
>> [[25869,0],0]-[[25869,1],0] mca_oob_tcp_msg_recv: readv failed: 
>> Connection reset by peer (104) [ngpu-a4-06:13356] 
>> [[25869,0],0]-[[25869,1],1] mca_oob_tcp_msg_recv: readv failed: 
>> Connection reset by peer (104)
>> 
>> 
>> Any idea what is wrong?
>> 
>> Thank you very much!
>> 
>> Max
>> 
>> -----Ursprüngliche Nachricht-----
>> Von: gromacs.org_gmx-users-bounces at maillist.sys.kth.se 
>> [mailto:gromacs.org_gmx-users-bounces at maillist.sys.kth.se] Im Auftrag 
>> von Ebert Maximilian
>> Gesendet: Mittwoch, 7. Januar 2015 14:43
>> An: gmx-users at gromacs.org
>> Betreff: Re: [gmx-users] Working on a GPU cluster with GROMACS 5
>> 
>> Hi Carsten,
>> 
>> thanks again for your reply. The why our cluster is setup is that you ask for GPUs using the ppn command and not CPUs. Therefore, I put 4 there. But to rule out the possibility that someone is actually using the note I called for 7 GPUs (so the entire note) but with GPU id just assign the first 4 to GROMACS. I still get the same error. I also tried -gpu_id 00 or -gpu_id 4444 to change the CPU and to only use a single GPU but I always get:
>> 
>> NOTE: You assigned GPUs to multiple MPI processes.
>> 
>> -------------------------------------------------------
>> Program gmx_mpi, VERSION 5.0.1
>> Source code file: 
>> /RQusagers/rqchpbib/stubbsda/gromacs-5.0.1/src/gromacs/gmxlib/cuda_too
>> ls/pmalloc_cuda.cu, line: 61
>> 
>> Fatal error:
>> cudaMallocHost of size 4 bytes failed: all CUDA-capable devices are 
>> busy or unavailable
>> 
>> For more information and tips for troubleshooting, please check the 
>> GROMACS website at http://www.gromacs.org/Documentation/Errors
>> -------------------------------------------------------
>> 
>> Error on rank 1, will try to stop all ranks Halting parallel program 
>> gmx_mpi on CPU 1 out of 4
>> 
>> -----Ursprüngliche Nachricht-----
>> Von: gromacs.org_gmx-users-bounces at maillist.sys.kth.se 
>> [mailto:gromacs.org_gmx-users-bounces at maillist.sys.kth.se] Im Auftrag 
>> von Carsten Kutzner
>> Gesendet: Mittwoch, 7. Januar 2015 14:13
>> An: gmx-users at gromacs.org
>> Betreff: Re: [gmx-users] Working on a GPU cluster with GROMACS 5
>> 
>> Hi Max,
>> 
>> On 07 Jan 2015, at 11:36, Ebert Maximilian <m.ebert at umontreal.ca> wrote:
>> 
>>> Hi Carsten,
>>> 
>>> thanks for your answer. I tried what you described and it is basically working except for letting multiple MPI workers use one GPU. In my setup I use 4 GPUs with 8 MPI workers and hence 8 CPUs and OpenMP 1.  This is how I start GROMACS:
>>> 
>>> mpirun -np 8 gmx_mpi mdrun -gpu_id 00112233 -v -x -deffnm run1ns -s 
>>> ../run1ns.tpr
>>> 
>>> and I submit this using:
>>> 
>>> qsub -q @test -lnodes=1:ppn=4 -lwalltime=1:00:00 gromacs_run_gpu
>> why are you using ppn=4? Shouldn't that be 8?
>> 
>>> 
>>> Now I get the following errors (the output is longer but to keep it shorter I omitted the rest):
>>> 
>>> Using 8 MPI processes
>>> Using 1 OpenMP thread per MPI process
>>> 
>>> 7 GPUs detected on host ngpu-a4-06:
>>> #0: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>> compatible
>>> #1: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>> compatible
>>> #2: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>> compatible
>>> #3: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>> compatible
>>> #4: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>> compatible
>>> #5: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>> compatible
>>> #6: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>> compatible
>>> 
>>> 4 GPUs user-selected for this run.
>>> Mapping of GPUs to the 8 PP ranks in this node: #0, #0, #1, #1, #2, 
>>> #2, #3, #3
>>> 
>>> NOTE: You assigned GPUs to multiple MPI processes.
>>> 
>>> -------------------------------------------------------
>>> Program gmx_mpi, VERSION 5.0.1
>>> Source code file: 
>>> /RQusagers/rqchpbib/stubbsda/gromacs-5.0.1/src/gromacs/gmxlib/cuda_to
>>> o
>>> ls/pmalloc_cuda.cu, line: 61
>>> 
>>> Fatal error:
>>> cudaMallocHost of size 4 bytes failed: all CUDA-capable devices are 
>>> busy or unavailable
>>> 
>> Could it be that someone else's processes are running on that node while Gromacs tries to use the GPUs? Maybe try to the the whole node, maybe even in interactive mode to play around.
>> 
>> Carsten
>> 
>>> For more information and tips for troubleshooting, please check the 
>>> GROMACS website at http://www.gromacs.org/Documentation/Errors
>>> -------------------------------------------------------
>>> 
>>> Error on rank 1, will try to stop all ranks Halting parallel program 
>>> gmx_mpi on CPU 1 out of 8
>>> 
>>> -------------------------------------------------------
>>> Program gmx_mpi, VERSION 5.0.1
>>> Source code file: 
>>> /RQusagers/rqchpbib/stubbsda/gromacs-5.0.1/src/gromacs/gmxlib/cuda_to
>>> o
>>> ls/pmalloc_cuda.cu, line: 61
>>> 
>>> Fatal error:
>>> cudaMallocHost of size 4 bytes failed: all CUDA-capable devices are 
>>> busy or unavailable
>>> 
>>> For more information and tips for troubleshooting, please check the 
>>> GROMACS website at http://www.gromacs.org/Documentation/Errors
>>> -------------------------------------------------------
>>> 
>>> Error on rank 3, will try to stop all ranks Halting parallel program 
>>> gmx_mpi on CPU 3 out of 8
>>> 
>>> -----Ursprüngliche Nachricht-----
>>> Von: gromacs.org_gmx-users-bounces at maillist.sys.kth.se
>>> [mailto:gromacs.org_gmx-users-bounces at maillist.sys.kth.se] Im Auftrag 
>>> von Carsten Kutzner
>>> Gesendet: Donnerstag, 18. Dezember 2014 17:27
>>> An: gmx-users at gromacs.org
>>> Betreff: Re: [gmx-users] Working on a GPU cluster with GROMACS 5
>>> 
>>> Hi Max,
>>> 
>>> On 18 Dec 2014, at 15:30, Ebert Maximilian <m.ebert at umontreal.ca> wrote:
>>> 
>>>> Dear list,
>>>> 
>>>> I am benchmarking my system on a GPU cluster with 6 GPU's and two quad core CPUs for each node. First I am wondering if there is any output which confirms how many CPUs and GPUs were used during the run? I find the output for GPUs in the log file but only for a single node. When I use multiple nodes why don't the other nodes show up in the log file as hosts? For instance in this example I used two nodes and claimed 4 GPUs each but got this in my log file:
>>>> 
>>>> 6 GPUs detected on host ngpu-a4-01:
>>>> #0: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>>> compatible
>>>> #1: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>>> compatible
>>>> #2: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>>> compatible
>>>> #3: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>>> compatible
>>>> #4: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>>> compatible
>>>> #5: NVIDIA GeForce GTX 580, compute cap.: 2.0, ECC:  no, stat: 
>>>> compatible
>>>> 
>>>> 4 GPUs auto-selected for this run.
>>>> Mapping of GPUs to the 4 PP ranks in this node: #0, #1, #2, #3
>>> This will be the same across all nodes. Gromacs will refuse to run if there are not enough GPUs on any of your other nodes.
>>> 
>>>> 
>>>> 
>>>> 
>>>> ngpu-a4-02 is not shown here. Any idea? The job was submitted in the following way:
>>>> 
>>>> qsub -q @test -lnodes=2:ppn=4 -lwalltime=1:00:00 gromacs_run_gpu
>>>> 
>>>> and the gromacs_run_gpu file:
>>>> 
>>>> #!/bin/csh
>>>> #
>>>> 
>>>> #PBS -o result_run10ns96-8.dat
>>>> #PBS -j oe
>>>> #PBS -W umask=022
>>>> #PBS -r n
>>>> 
>>>> cd 8_gpu
>>>> 
>>>> module add CUDA
>>>> module load gromacs/5.0.1-gpu
>>>> 
>>>> mpirun gmx_mpi mdrun -v -x -deffnm 10ns_rep1-8GPU
>>>> 
>>>> 
>>>> Another question I had was how can I define the number of CPUs and check if they were really used?
>>> Use -ntomp to control how many OpenMP threads each of your MPI processes will have.
>>> This way you can make use of all cores you have on each node.
>>> 
>>>> I can't find any information about the number of CPUs in the log file.
>>> Look for
>>> "Using . MPI processes"
>>> "Using . OpenMP threads per MPI process"
>>> in the log file.
>>> 
>>>> I would also like to try combinations like 4 CPUs + 1 GPU
>>> You can use the -gpu_id switch to supply a list of eligible GPUs (see mdrun -h).
>>> If you just want to use the first GPU on you node with, e.g. 4 MPI processes, use -gpu_id 0000.
>>> 
>>> Best,
>>> Carsten
>>> 
>>> 
>>> 
>>>> or 2 CPUs + 2 GPU. How do I set this up?
>>>> 
>>>> Thank you very much for your help,
>>>> 
>>>> Max
>>>> 
>>>> --
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>>> 
>>> 
>>> --
>>> Dr. Carsten Kutzner
>>> Max Planck Institute for Biophysical Chemistry Theoretical and 
>>> Computational Biophysics Am Fassberg 11, 37077 Goettingen, Germany 
>>> Tel. +49-551-2012313, Fax: +49-551-2012302 
>>> http://www.mpibpc.mpg.de/grubmueller/kutzner
>>> http://www.mpibpc.mpg.de/grubmueller/sppexa
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>> 
>> 
>> --
>> Dr. Carsten Kutzner
>> Max Planck Institute for Biophysical Chemistry Theoretical and 
>> Computational Biophysics Am Fassberg 11, 37077 Goettingen, Germany 
>> Tel. +49-551-2012313, Fax: +49-551-2012302 
>> http://www.mpibpc.mpg.de/grubmueller/kutzner
>> http://www.mpibpc.mpg.de/grubmueller/sppexa
>> 
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> 
> 
> --
> Dr. Carsten Kutzner
> Max Planck Institute for Biophysical Chemistry Theoretical and Computational Biophysics Am Fassberg 11, 37077 Goettingen, Germany Tel. +49-551-2012313, Fax: +49-551-2012302 http://www.mpibpc.mpg.de/grubmueller/kutzner
> http://www.mpibpc.mpg.de/grubmueller/sppexa
> 
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--
Dr. Carsten Kutzner
Max Planck Institute for Biophysical Chemistry
Theoretical and Computational Biophysics
Am Fassberg 11, 37077 Goettingen, Germany
Tel. +49-551-2012313, Fax: +49-551-2012302
http://www.mpibpc.mpg.de/grubmueller/kutzner
http://www.mpibpc.mpg.de/grubmueller/sppexa