Re: [gmx-users] cpu/gpu utilization

2018-03-02 Thread Szilárd Páll
On Fri, Mar 2, 2018 at 1:57 PM, Mahmood Naderan 
wrote:

> Sorry for the confusion. My fault...
> I saw my previous post and found that I missed something. In fact, I
> couldn't run "-pme gpu".
>
> So, once again, I ran all the commands and uploaded the log files
>
>
> gmx mdrun -nobackup -nb cpu -pme cpu -deffnm md_0_1
> https://pastebin.com/RNT4XJy8
>
>
> gmx mdrun -nobackup -nb cpu -pme gpu -deffnm md_0_1
> https://pastebin.com/7BQn8R7g
> This run shows an error on the screen which is not shown in the log file.
> So please also see https://pastebin.com/KHg6FkBz


That's expected, only offloading PME is not supported.,different offload
modes supported are:
- nonbonded offload
- nonbonded + full PME offload
- nonbonded + PME mixed mode offload (FFTs run on the CPU)



>
>
>
> gmx mdrun -nobackup -nb gpu -pme cpu -deffnm md_0_1
> https://pastebin.com/YXYj23tB
>
>
>
> gmx mdrun -nobackup -nb gpu -pme gpu -deffnm md_0_1
> https://pastebin.com/P3X4mE5y
>
>
> offloadable
>
>
> From the results, it seems that running the pme on the cpu is better than
> gpu. The fastest command here is -nb gpu -pme cpu
>

Right, same as before except that it looks like this time is ~5% slower
(likely the auto-tuner did not manage two switch to the ideal setting).


>
>
> Still I have the question that while GPU is utilized, the CPU is also
> busy. So, I was thinking that the source code uses cudaDeviceSynchronize()
> where the CPU enters a busy loop.
>

Yes, CPU and GPU run concurrently and work on independent tasks, when the
CPU is done it has to wait for the GPU before it can proceed with
constraints/integration.

To get a better overview, please read some of the GROMACS papers (
http://www.gromacs.org/Gromacs_papers) or tldr see https://goo.gl/AGv6hy
(around slides 12-15).

Cheers,
--
Szilárd


>
>
>
> Regards,
> Mahmood
>
>
>
>
>
>
> On Friday, March 2, 2018, 3:24:41 PM GMT+3:30, Szilárd Páll <
> pall.szil...@gmail.com> wrote:
>
>
>
>
>
> Once again, full log files, please, not partial cut-and-paste, please.
>
> Also, you misread something because your previous logs show:
> -nb cpu -pme gpu: 56.4 ns/day
> -nb cpu -pme gpu -pmefft cpu 64.6 ns/day
> -nb cpu -pme cpu 67.5 ns/day
>
> So both mixed mode PME and PME on CPU are faster, the latter slightly
> faster than the former.
>
> This is about as much as you can do, I think. Your GPU is just too slow to
> get more performance out of it and the runs are GPU-bound. You might be
> able to get a bit more performance with some tweaks (compile mdrun with
> AVX2_256, use a newer fftw, use a newer gcc), but expect marginal gains.
>
> Cheers,
>
> --
> Szilárd
>
>
>
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Re: [gmx-users] cpu/gpu utilization

2018-03-02 Thread Mahmood Naderan
Sorry for the confusion. My fault...
I saw my previous post and found that I missed something. In fact, I couldn't 
run "-pme gpu".

So, once again, I ran all the commands and uploaded the log files


gmx mdrun -nobackup -nb cpu -pme cpu -deffnm md_0_1
https://pastebin.com/RNT4XJy8


gmx mdrun -nobackup -nb cpu -pme gpu -deffnm md_0_1
https://pastebin.com/7BQn8R7g
This run shows an error on the screen which is not shown in the log file. So 
please also see https://pastebin.com/KHg6FkBz



gmx mdrun -nobackup -nb gpu -pme cpu -deffnm md_0_1
https://pastebin.com/YXYj23tB



gmx mdrun -nobackup -nb gpu -pme gpu -deffnm md_0_1
https://pastebin.com/P3X4mE5y





From the results, it seems that running the pme on the cpu is better than gpu. 
The fastest command here is -nb gpu -pme cpu


Still I have the question that while GPU is utilized, the CPU is also busy. So, 
I was thinking that the source code uses cudaDeviceSynchronize() where the CPU 
enters a busy loop.



Regards,
Mahmood






On Friday, March 2, 2018, 3:24:41 PM GMT+3:30, Szilárd Páll 
 wrote: 





Once again, full log files, please, not partial cut-and-paste, please.

Also, you misread something because your previous logs show:
-nb cpu -pme gpu: 56.4 ns/day
-nb cpu -pme gpu -pmefft cpu 64.6 ns/day
-nb cpu -pme cpu 67.5 ns/day

So both mixed mode PME and PME on CPU are faster, the latter slightly faster 
than the former.

This is about as much as you can do, I think. Your GPU is just too slow to get 
more performance out of it and the runs are GPU-bound. You might be able to get 
a bit more performance with some tweaks (compile mdrun with AVX2_256, use a 
newer fftw, use a newer gcc), but expect marginal gains.

Cheers,

--
Szilárd


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Re: [gmx-users] cpu/gpu utilization

2018-03-02 Thread Szilárd Páll
Once again, full log files, please, not partial cut-and-paste, please.

Also, you misread something because your previous logs show:
-nb cpu -pme gpu: 56.4 ns/day
-nb cpu -pme gpu -pmefft cpu 64.6 ns/day
-nb cpu -pme cpu 67.5 ns/day

So both mixed mode PME and PME on CPU are faster, the latter slightly
faster than the former.

This is about as much as you can do, I think. Your GPU is just too slow to
get more performance out of it and the runs are GPU-bound. You might be
able to get a bit more performance with some tweaks (compile mdrun with
AVX2_256, use a newer fftw, use a newer gcc), but expect marginal gains.

Cheers,

--
Szilárd

On Fri, Mar 2, 2018 at 11:00 AM, Mahmood Naderan 
wrote:

> Command is "gmx mdrun -nobackup -pme cpu -nb gpu -deffnm md_0_1" and the
> log says
>
>  R E A L   C Y C L E   A N D   T I M E   A C C O U N T I N G
>
> On 1 MPI rank, each using 16 OpenMP threads
>
>  Computing:  Num   Num  CallWall time Giga-Cycles
>  Ranks Threads  Count  (s) total sum%
> 
> -
>  Neighbor search1   16501   0.972 55.965   0.8
>  Launch GPU ops.1   16  50001   2.141123.301   1.7
>  Force  1   16  50001   4.019231.486   3.1
>  PME mesh   1   16  50001  40.695   2344.171  31.8
>  Wait GPU NB local  1   16  50001  60.155   3465.079  47.0
>  NB X/F buffer ops. 1   16  99501   7.342422.902   5.7
>  Write traj.1   16 11   0.246 14.184   0.2
>  Update 1   16  50001   3.480200.461   2.7
>  Constraints1   16  50001   5.831335.878   4.6
>  Rest   3.159181.963   2.5
> 
> -
>  Total128.039   7375.390 100.0
> 
> -
>  Breakdown of PME mesh computation
> 
> -
>  PME spread 1   16  50001  17.086984.209  13.3
>  PME gather 1   16  50001  12.534722.007   9.8
>  PME 3D-FFT 1   16 12   9.956573.512   7.8
>  PME solve Elec 1   16  50001   0.779 44.859   0.6
> 
> -
>
>Core t (s)   Wall t (s)(%)
>Time: 2048.617  128.039 1600.0
>  (ns/day)(hour/ns)
> Performance:   67.4810.356
>
>
>
>
>
>
> While the command is "", I see that the gpu is utilized about 10% and the
> log file says:
>
>  R E A L   C Y C L E   A N D   T I M E   A C C O U N T I N G
>
> On 1 MPI rank, each using 16 OpenMP threads
>
>  Computing:  Num   Num  CallWall time Giga-Cycles
>  Ranks Threads  Count  (s) total sum%
> 
> -
>  Neighbor search1   16   1251   6.912398.128   2.3
>  Force  1   16  50001 210.689  12135.653  70.4
>  PME mesh   1   16  50001  46.869   2699.656  15.7
>  NB X/F buffer ops. 1   16  98751  22.315   1285.360   7.5
>  Write traj.1   16 11   0.216 12.447   0.1
>  Update 1   16  50001   4.382252.386   1.5
>  Constraints1   16  50001   6.035347.601   2.0
>  Rest   1.666 95.933   0.6
> 
> -
>  Total299.083  17227.165 100.0
> 
> -
>  Breakdown of PME mesh computation
> 
> -
>  PME spread 1   16  50001  21.505   1238.693   7.2
>  PME gather 1   16  50001  12.089696.333   4.0
>  PME 3D-FFT 1   16 12  11.627669.705   3.9
>  PME solve Elec 1   16  50001   0.965 55.598   0.3
> 
> -
>
>Core t (s)   Wall t (s)(%)
>Time: 4785.326  299.083 1600.0
>  (ns/day)(hour/ns)
> Performance:   28.8890.831
>
>
>
>
> Using GPU is still better than using CPU alone. However, I see that while
> GPU is utilized, the 

Re: [gmx-users] cpu/gpu utilization

2018-03-02 Thread Mahmood Naderan
Command is "gmx mdrun -nobackup -pme cpu -nb gpu -deffnm md_0_1" and the log 
says

 R E A L   C Y C L E   A N D   T I M E   A C C O U N T I N G

On 1 MPI rank, each using 16 OpenMP threads

 Computing:  Num   Num  Call    Wall time Giga-Cycles
 Ranks Threads  Count  (s) total sum    %
-
 Neighbor search    1   16    501   0.972 55.965   0.8
 Launch GPU ops.    1   16  50001   2.141    123.301   1.7
 Force  1   16  50001   4.019    231.486   3.1
 PME mesh   1   16  50001  40.695   2344.171  31.8
 Wait GPU NB local  1   16  50001  60.155   3465.079  47.0
 NB X/F buffer ops. 1   16  99501   7.342    422.902   5.7
 Write traj.    1   16 11   0.246 14.184   0.2
 Update 1   16  50001   3.480    200.461   2.7
 Constraints    1   16  50001   5.831    335.878   4.6
 Rest   3.159    181.963   2.5
-
 Total    128.039   7375.390 100.0
-
 Breakdown of PME mesh computation
-
 PME spread 1   16  50001  17.086    984.209  13.3
 PME gather 1   16  50001  12.534    722.007   9.8
 PME 3D-FFT 1   16 12   9.956    573.512   7.8
 PME solve Elec 1   16  50001   0.779 44.859   0.6
-

   Core t (s)   Wall t (s)    (%)
   Time: 2048.617  128.039 1600.0
 (ns/day)    (hour/ns)
Performance:   67.481    0.356






While the command is "", I see that the gpu is utilized about 10% and the log 
file says:

 R E A L   C Y C L E   A N D   T I M E   A C C O U N T I N G

On 1 MPI rank, each using 16 OpenMP threads

 Computing:  Num   Num  Call    Wall time Giga-Cycles
 Ranks Threads  Count  (s) total sum    %
-
 Neighbor search    1   16   1251   6.912    398.128   2.3
 Force  1   16  50001 210.689  12135.653  70.4
 PME mesh   1   16  50001  46.869   2699.656  15.7
 NB X/F buffer ops. 1   16  98751  22.315   1285.360   7.5
 Write traj.    1   16 11   0.216 12.447   0.1
 Update 1   16  50001   4.382    252.386   1.5
 Constraints    1   16  50001   6.035    347.601   2.0
 Rest   1.666 95.933   0.6
-
 Total    299.083  17227.165 100.0
-
 Breakdown of PME mesh computation
-
 PME spread 1   16  50001  21.505   1238.693   7.2
 PME gather 1   16  50001  12.089    696.333   4.0
 PME 3D-FFT 1   16 12  11.627    669.705   3.9
 PME solve Elec 1   16  50001   0.965 55.598   0.3
-

   Core t (s)   Wall t (s)    (%)
   Time: 4785.326  299.083 1600.0
 (ns/day)    (hour/ns)
Performance:   28.889    0.831




Using GPU is still better than using CPU alone. However, I see that while GPU 
is utilized, the CPU is also busy. So, I was thinking that the source code uses 
cudaDeviceSynchronize() where the CPU enters a busy loop.

Regards,
Mahmood 

On Friday, March 2, 2018, 11:37:11 AM GMT+3:30, Magnus Lundborg 
 wrote:  
 
 Have you tried the mdrun options:

-pme cpu -nb gpu
-pme cpu -nb cpu

Cheers,

Magnus

  
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Re: [gmx-users] cpu/gpu utilization

2018-03-02 Thread Magnus Lundborg

Have you tried the mdrun options:

-pme cpu -nb gpu
-pme cpu -nb cpu

Cheers,

Magnus

On 2018-03-02 07:55, Mahmood Naderan wrote:

If you mean [1], then yes I read that and that recommends to use Verlet for the 
new algorithm depicted in  figures. At least that is my understanding about 
offloading. If I read the wrong document or you mean there is also some other 
options, please let me know.

[1] http://www.gromacs.org/GPU_acceleration





Regards,
Mahmood

 On Thursday, March 1, 2018, 6:35:46 PM GMT+3:30, Szilárd Páll 
 wrote:
  
  Have you read the "Types of GPU tasks" section of the user guide?


--
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Re: [gmx-users] cpu/gpu utilization

2018-03-01 Thread Mahmood Naderan
If you mean [1], then yes I read that and that recommends to use Verlet for the 
new algorithm depicted in  figures. At least that is my understanding about 
offloading. If I read the wrong document or you mean there is also some other 
options, please let me know.

[1] http://www.gromacs.org/GPU_acceleration





Regards,
Mahmood 

On Thursday, March 1, 2018, 6:35:46 PM GMT+3:30, Szilárd Páll 
 wrote:  
 
 Have you read the "Types of GPU tasks" section of the user guide?

--
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Re: [gmx-users] cpu/gpu utilization

2018-03-01 Thread Szilárd Páll
Have you read the "Types of GPU tasks" section of the user guide?

--
Szilárd

On Thu, Mar 1, 2018 at 3:34 PM, Mahmood Naderan 
wrote:

> >Again, first and foremost, try running PME on the CPU, your 8-core Ryzen
> will be plenty fast for that.
>
>
> Since I am a computer guy and not a chemist, the question may be noob!
> What do you mean exactly by running pme on cpu?
>
> You mean "-nb cpu"? or you mean setting cut-off to Group instead of Verlet
> (latter is used for GPU only)?
>
>
> Regards,
> Mahmood
>
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Re: [gmx-users] cpu/gpu utilization

2018-03-01 Thread Mahmood Naderan
>Again, first and foremost, try running PME on the CPU, your 8-core Ryzen will 
>be plenty fast for that.


Since I am a computer guy and not a chemist, the question may be noob!
What do you mean exactly by running pme on cpu?

You mean "-nb cpu"? or you mean setting cut-off to Group instead of Verlet 
(latter is used for GPU only)?


Regards,
Mahmood
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Re: [gmx-users] cpu/gpu utilization

2018-03-01 Thread Szilárd Páll
No, that does not seem to help much because the GPU is rather slow at
getting the PME Spread done (there's still 12.6% wait for the GPU to finish
that), and there are slight overheads that end up hurting performance.

Again, first and foremost, try running PME on the CPU, your 8-core Ryzen
will be plenty fast for that.

--
Szilárd

On Thu, Mar 1, 2018 at 2:22 PM, Mahmood Naderan 
wrote:

> >- as noted above try offloading only the nonbondeds (or possibly the
> hybrid PME mode -pmefft cpu)
>
> So, with "-pmefft cpu", I don't see any good impact!
> See the log at https://pastebin.com/RTYaKSne
>
> I will use other options to see the effect.
>
>
> Regards,
> Mahmood
>
>
>
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Re: [gmx-users] cpu/gpu utilization

2018-03-01 Thread Mahmood Naderan
>- as noted above try offloading only the nonbondeds (or possibly the hybrid 
>PME mode -pmefft cpu)

So, with "-pmefft cpu", I don't see any good impact!See the log at 
https://pastebin.com/RTYaKSne

I will use other options to see the effect.


Regards,
Mahmood 

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Re: [gmx-users] cpu/gpu utilization

2018-03-01 Thread Szilárd Páll
On Thu, Mar 1, 2018 at 8:25 AM, Mahmood Naderan 
wrote:

> >(try the other parallel modes)
>
> Do you mean OpenMP and MPI?
>

No, I meant different offload modes.


>
> >- as noted above try offloading only the nonbondeds (or possibly the
> hybrid PME mode -pmefft cpu)
>
> May I know how? Which part of the documentation says about that?
>

http://manual.gromacs.org/documentation/current/user-guide/mdrun-performance.html#types-of-gpu-tasks
http://manual.gromacs.org/documentation/current/onlinehelp/gmx-mdrun.html


>
>
> Regards,
> Mahmood
>
>
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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Mahmood Naderan
>(try the other parallel modes)

Do you mean OpenMP and MPI?


>- as noted above try offloading only the nonbondeds (or possibly the hybrid 
>PME mode -pmefft cpu)

May I know how? Which part of the documentation says about that?


Regards,
Mahmood

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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Szilárd Páll
PS:
Care to know what can you do?
- as noted above try offloading only the nonbondeds (or possibly the hybrid
PME mode -pmefft cpu)
- check if your GPU has application clocks that can be bumped
- if you have the means, consider getting a bit faster GPU; the Quadro
M2000 in your machine is both slightly dated and low-end  similar board as
the GTX 950



--
Szilárd

On Wed, Feb 28, 2018 at 10:26 PM, Szilárd Páll 
wrote:

> Thanks!
>
> Looking at the log file, as I guessed earlier, you can see the following:
>
> - Given that you have a rather low-end GPU and a fairly fast workstation
> CPU the run is *very* GPU-bound: the CPU spends 16.4 + 54.2 = 70.6% waiting
> for the GPU (see lines 628 and 630)
>
> - this means that the default behavior of offloading both the nonbonded
> and PME tasks to the GPU is not beneficial (try the other parallel modes)
>
> - mdrun is still using 8 cores / 16 threads *for the parts of the run that
> require it* (Bonded forces (2.7%), Integration / Constraints (2.6 % / 4.9
> %) etc.), but as this takes <30% of the runtime, that gives you your
> average of 4.5 utilization (0.3*16 = 4.8). That you "see" 9 threads active
> is just the averaging/sampling effect of from your minitoring tools.
>
> Cheers,
>
> --
> Szilárd
>
> On Wed, Feb 28, 2018 at 10:12 PM, Mahmood Naderan 
> wrote:
>
>> >The list does not accept attachments, so please use a file sharing or
>> content sharing website so >everyone can see your data and has the context.
>>
>> I uploaded here
>>
>> https://pastebin.com/RCkkFXPx
>>
>>
>>
>> Regards,
>> Mahmood
>>
>>
>
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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Szilárd Páll
Thanks!

Looking at the log file, as I guessed earlier, you can see the following:

- Given that you have a rather low-end GPU and a fairly fast workstation
CPU the run is *very* GPU-bound: the CPU spends 16.4 + 54.2 = 70.6% waiting
for the GPU (see lines 628 and 630)

- this means that the default behavior of offloading both the nonbonded and
PME tasks to the GPU is not beneficial (try the other parallel modes)

- mdrun is still using 8 cores / 16 threads *for the parts of the run that
require it* (Bonded forces (2.7%), Integration / Constraints (2.6 % / 4.9
%) etc.), but as this takes <30% of the runtime, that gives you your
average of 4.5 utilization (0.3*16 = 4.8). That you "see" 9 threads active
is just the averaging/sampling effect of from your minitoring tools.

Cheers,

--
Szilárd

On Wed, Feb 28, 2018 at 10:12 PM, Mahmood Naderan 
wrote:

> >The list does not accept attachments, so please use a file sharing or
> content sharing website so >everyone can see your data and has the context.
>
> I uploaded here
>
> https://pastebin.com/RCkkFXPx
>
>
>
> Regards,
> Mahmood
>
>
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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Mahmood Naderan
>The list does not accept attachments, so please use a file sharing or content 
>sharing website so >everyone can see your data and has the context.

I uploaded here

https://pastebin.com/RCkkFXPx



Regards,
Mahmood

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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Szilárd Páll
The list does not accept attachments, so please use a file sharing or
content sharing website so everyone can see your data and has the context.

--
Szilárd

On Wed, Feb 28, 2018 at 7:51 PM, Mahmood Naderan 
wrote:

> >Additionally, you still have not provided the *mdrun log file* I
> requested. top output is not what I asked for.
> See the attached file.
>
>
> Regards,
> Mahmood
>
>
>
>
>
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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Mahmood Naderan
>Additionally, you still have not provided the *mdrun log file* I requested. 
>top output is not what I asked for.
See the attached file.


Regards,
Mahmood




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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Szilárd Páll
Your run is probably GPU-bound because you have a rather slow GPU and as
per new mdrun defaults both PME and nonbondeds are offloaded which may not
be ideal for your case. Try the different offload modes to see which one is
best on your hardware.

Additionally, you still have not provided the *mdrun log file* I requested.
top output is not what I asked for.




--
Szilárd

On Wed, Feb 28, 2018 at 4:47 PM, Mahmood Naderan 
wrote:

> I forgot to say that gromacs reports
>
> No option -multi
> Using 1 MPI thread
> Using 16 OpenMP threads
>
> 1 GPU auto-selected for this run.
> Mapping of GPU IDs to the 2 GPU tasks in the 1 rank on this node:
>   PP:0,PME:0
>
> NOTE: GROMACS was configured without NVML support hence it can not exploit
>   application clocks of the detected Quadro M2000 GPU to improve
> performance.
>
>
>
>
>
>
> Regards,
> Mahmood
>
>
> On Wednesday, February 28, 2018, 7:15:13 PM GMT+3:30, Mahmood Naderan <
> nt_mahm...@yahoo.com> wrote:
>
>
> By runing
>
> gmx mdrun -nb gpu -deffnm md_0_1
>
>
> I see the following outputs
>
>
> $ top -b  | head -n 10
> top - 19:14:10 up 7 min,  1 user,  load average: 4.54, 1.40, 0.54
> Tasks: 344 total,   1 running, 343 sleeping,   0 stopped,   0 zombie
> %Cpu(s):  7.1 us,  0.5 sy,  0.0 ni, 91.9 id,  0.4 wa,  0.0 hi,  0.0 si,
> 0.0 st
> KiB Mem : 16438496 total, 13462876 free,  1968196 used,  1007424 buff/cache
> KiB Swap: 31250428 total, 31250428 free,0 used. 14054796 avail Mem
>
>   PID USER  PR  NIVIRTRESSHR S  %CPU %MEM TIME+ COMMAND
>  3604 mahmood   20   0 30.519g 525812 128788 S 918.8  3.2   6:58.38 gmx
>  1180 root  20   0  324688  69384  49712 S   6.2  0.4   0:14.41 Xorg
>  1450 mahmood   20   0  210228   7856   7192 S   6.2  0.0   0:00.17
> ibus-engin+
>
>
>
> $ nvidia-smi
> Wed Feb 28 19:14:35 2018
> +---
> --+
> | NVIDIA-SMI 384.81 Driver Version:
> 384.81|
> |---+--+
> --+
> | GPU  NamePersistence-M| Bus-IdDisp.A | Volatile Uncorr.
> ECC |
> | Fan  Temp  Perf  Pwr:Usage/Cap| Memory-Usage | GPU-Util  Compute
> M. |
> |===+==+
> ==|
> |   0  Quadro M2000Off  | :23:00.0  On |
> N/A |
> | 65%   64CP058W /  75W |292MiB /  4035MiB | 93%
> Default |
> +---+--+
> --+
>
>
> +---
> --+
> | Processes:   GPU
> Memory |
> |  GPU   PID   Type   Process name
> Usage  |
> |===
> ==|
> |0  1180  G   /usr/lib/xorg/Xorg
> 141MiB |
> |0  1651  G   compiz
> 46MiB |
> |0  3604  C   gmx
> 90MiB |
> +---
> --+
>
>
>
>
>
> Any idea?
>
>
> Regards,
> Mahmood
>
>
> On Monday, February 26, 2018, 10:52:40 PM GMT+3:30, Szilárd Páll <
> pall.szil...@gmail.com> wrote:
>
>
> Hi,
>
> Please provide details, e.g. the full log so we know what version, on what
> hardware, settings etc. you're running.
>
>
>
> --
> Szilárd
>
>
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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Mahmood Naderan
I forgot to say that gromacs reports
No option -multi
Using 1 MPI thread
Using 16 OpenMP threads 

1 GPU auto-selected for this run.
Mapping of GPU IDs to the 2 GPU tasks in the 1 rank on this node:
  PP:0,PME:0

NOTE: GROMACS was configured without NVML support hence it can not exploit
  application clocks of the detected Quadro M2000 GPU to improve 
performance.






Regards,
Mahmood 

On Wednesday, February 28, 2018, 7:15:13 PM GMT+3:30, Mahmood Naderan 
 wrote:  
 
 By runing
gmx mdrun -nb gpu -deffnm md_0_1

I see the following outputs

$ top -b  | head -n 10
top - 19:14:10 up 7 min,  1 user,  load average: 4.54, 1.40, 0.54
Tasks: 344 total,   1 running, 343 sleeping,   0 stopped,   0 zombie
%Cpu(s):  7.1 us,  0.5 sy,  0.0 ni, 91.9 id,  0.4 wa,  0.0 hi,  0.0 si,  0.0 st
KiB Mem : 16438496 total, 13462876 free,  1968196 used,  1007424 buff/cache
KiB Swap: 31250428 total, 31250428 free,    0 used. 14054796 avail Mem 

  PID USER  PR  NI    VIRT    RES    SHR S  %CPU %MEM TIME+ COMMAND
 3604 mahmood   20   0 30.519g 525812 128788 S 918.8  3.2   6:58.38 gmx
 1180 root  20   0  324688  69384  49712 S   6.2  0.4   0:14.41 Xorg
 1450 mahmood   20   0  210228   7856   7192 S   6.2  0.0   0:00.17 ibus-engin+



$ nvidia-smi 
Wed Feb 28 19:14:35 2018   
+-+
| NVIDIA-SMI 384.81 Driver Version: 384.81    |
|---+--+--+
| GPU  Name    Persistence-M| Bus-Id    Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap| Memory-Usage | GPU-Util  Compute M. |
|===+==+==|
|   0  Quadro M2000    Off  | :23:00.0  On |  N/A |
| 65%   64C    P0    58W /  75W |    292MiB /  4035MiB | 93%  Default |
+---+--+--+
   
+-+
| Processes:   GPU Memory |
|  GPU   PID   Type   Process name Usage  |
|=|
|    0  1180  G   /usr/lib/xorg/Xorg   141MiB |
|    0  1651  G   compiz    46MiB |
|    0  3604  C   gmx   90MiB |
+-+





Any idea?


Regards,
Mahmood 

On Monday, February 26, 2018, 10:52:40 PM GMT+3:30, Szilárd Páll 
 wrote:  
 
 Hi,
Please provide details, e.g. the full log so we know what version, on what 
hardware, settings etc. you're running.


--
Szilárd

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Re: [gmx-users] cpu/gpu utilization

2018-02-28 Thread Mahmood Naderan
By runing
gmx mdrun -nb gpu -deffnm md_0_1

I see the following outputs

$ top -b  | head -n 10
top - 19:14:10 up 7 min,  1 user,  load average: 4.54, 1.40, 0.54
Tasks: 344 total,   1 running, 343 sleeping,   0 stopped,   0 zombie
%Cpu(s):  7.1 us,  0.5 sy,  0.0 ni, 91.9 id,  0.4 wa,  0.0 hi,  0.0 si,  0.0 st
KiB Mem : 16438496 total, 13462876 free,  1968196 used,  1007424 buff/cache
KiB Swap: 31250428 total, 31250428 free,    0 used. 14054796 avail Mem 

  PID USER  PR  NI    VIRT    RES    SHR S  %CPU %MEM TIME+ COMMAND
 3604 mahmood   20   0 30.519g 525812 128788 S 918.8  3.2   6:58.38 gmx
 1180 root  20   0  324688  69384  49712 S   6.2  0.4   0:14.41 Xorg
 1450 mahmood   20   0  210228   7856   7192 S   6.2  0.0   0:00.17 ibus-engin+



$ nvidia-smi 
Wed Feb 28 19:14:35 2018   
+-+
| NVIDIA-SMI 384.81 Driver Version: 384.81    |
|---+--+--+
| GPU  Name    Persistence-M| Bus-Id    Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap| Memory-Usage | GPU-Util  Compute M. |
|===+==+==|
|   0  Quadro M2000    Off  | :23:00.0  On |  N/A |
| 65%   64C    P0    58W /  75W |    292MiB /  4035MiB | 93%  Default |
+---+--+--+
   
+-+
| Processes:   GPU Memory |
|  GPU   PID   Type   Process name Usage  |
|=|
|    0  1180  G   /usr/lib/xorg/Xorg   141MiB |
|    0  1651  G   compiz    46MiB |
|    0  3604  C   gmx   90MiB |
+-+





Any idea?


Regards,
Mahmood 

On Monday, February 26, 2018, 10:52:40 PM GMT+3:30, Szilárd Páll 
 wrote:  
 
 Hi,
Please provide details, e.g. the full log so we know what version, on what 
hardware, settings etc. you're running.


--
Szilárd
  
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Re: [gmx-users] cpu/gpu utilization

2018-02-26 Thread Szilárd Páll
Hi,

Please provide details, e.g. the full log so we know what version, on what
hardware, settings etc. you're running.



--
Szilárd

On Mon, Feb 26, 2018 at 8:02 PM, Mahmood Naderan 
wrote:

> Hi,
>
> While the cut-off is set to Verlet and I run "gmx mdrun -nb gpu -deffnm
> input_md", I see that 9 threads out of total logical 16 threads are running
> on the cpu while the gpu is utilized. The gmx also says
>
>
> No option -multi
> Using 1 MPI thread
> Using 16 OpenMP threads
>
>
> I want to know, why 9 threads are running?
> Is that normal? Ryzen 1800x has 8 physical cores.
>
>
> Regards,
> Mahmood
> --
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[gmx-users] cpu/gpu utilization

2018-02-26 Thread Mahmood Naderan
Hi,

While the cut-off is set to Verlet and I run "gmx mdrun -nb gpu -deffnm 
input_md", I see that 9 threads out of total logical 16 threads are running on 
the cpu while the gpu is utilized. The gmx also says


No option -multi
Using 1 MPI thread
Using 16 OpenMP threads 


I want to know, why 9 threads are running? 
Is that normal? Ryzen 1800x has 8 physical cores. 


Regards,
Mahmood
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