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cluster:182 [2019/08/12 16:45]
hmeij07 [Lammps] 		cluster:182 [2019/12/13 13:33] (current)
hmeij07
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 **[[cluster:0|Back]]** **[[cluster:0|Back]]**
  
 + 
 ==== P100 vs RTX 6000 & T4 ==== ==== P100 vs RTX 6000 & T4 ====
  
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 |  DPFP  |  5.21|  18.35|  0.75|  0.35|  1.29| |  DPFP  |  5.21|  18.35|  0.75|  0.35|  1.29|
 |  SXFP  |  11.82|  37.44|  17.05|  7.01|  18.91| |  SXFP  |  11.82|  37.44|  17.05|  7.01|  18.91|
-|  SFFP  |  11.91|  40.98|  9.92|  4.35|  16.22|+|  SPFP  |  11.91|  40.98|  9.92|  4.35|  16.22|
  
 Like last testing outcome, in the SFFP precision mode it is best to run four individual jobs, one per GPU (mpi=1, gpu=1). Best performance is the P100 at 47.64 vs the RTX at 39.69 ns/day per node. The T4 runs about 1/3 as fast and really falters in DPFP precision mode. But in SXFP (experimental) precision mode the T4 makes up in performance.  Like last testing outcome, in the SFFP precision mode it is best to run four individual jobs, one per GPU (mpi=1, gpu=1). Best performance is the P100 at 47.64 vs the RTX at 39.69 ns/day per node. The T4 runs about 1/3 as fast and really falters in DPFP precision mode. But in SXFP (experimental) precision mode the T4 makes up in performance. 
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 Precision for GPU calculations Precision for GPU calculations
  
-  * DD -D_DOUBLE_DOUBLE  # Double precision for all calculations +  * [DD] -D_DOUBLE_DOUBLE  # Double precision for all calculations 
-  * SD -D_SINGLE_DOUBLE  # Accumulation of forces, etc. in double +  * [SD] -D_SINGLE_DOUBLE  # Accumulation of forces, etc. in double 
-  * SS -D_SINGLE_SINGLE  # Single precision for all calculations +  * [SS] -D_SINGLE_SINGLE  # Single precision for all calculations
  
  
 ^  tau/day  ^  P100[1]  ^  P100[4]  ^  RTX[1]  ^  T4[1]  ^  T4[4]  ^  Notes  ^ ^  tau/day  ^  P100[1]  ^  P100[4]  ^  RTX[1]  ^  T4[1]  ^  T4[4]  ^  Notes  ^
-|  DD  |  856669.660|  ?|  600048.822|  518164.721|  1098621.095|  | +|  DD  |  856,669|  ?|  600,048|  518,164|  1,098,621|  | 
-|  SD  |  981897.313|  ?|  916225.855|  881247.547|  2294344.194|  | +|  SD  |  981,897|  ?|  916,225|  881,247|  2,294,344|  | 
-|  SS  |  1050796.986|  ?|  1035041.889|  1021477.986|  2541435.426|  |+|  SS  |  1,050,796|  ?|  1,035,041|  1,021,477|  2,541,435|  | 
 + 
 +Forgot run run the 4 GPU P100 scenarios, deh. 
 + 
 +As with Amber, it is best to run one job per GPU to achieve max node performance. Depending on problem set performance can be boosted by requesting more MPI threads. In previous tests the P100 in double_double precision mode achieved 2.7 million tau/day, so these results are surprising. The RTX 6000 does a decent job of keeping up with the P100. 
 + 
 +But the T4 shines in this application. The mixed or single precision modes compete well given the T4's price and  wattage consumption. 
 + 
 +==== Gromacs ==== 
 + 
 +Gromacs was build on each of the nodes locally letting it select the optimal CPU (AVX, SSE) and GPU accelerators. "GROMACS simulations are normally run in “mixed” floating-point precision, which is suited for the use of single precision in FFTW. " The ''cmake'' flag ''-DGMX_BUILD_OWN_FFTW=ON'' yields a mixed precision compilation which is recommended. Then we ran multidir options 01-04 on single GPU, and 01-08 and 01-16 on all 4 GPUs when possible. 
 + 
 + 
 +^  ns/day  ^  P100[1]  ^  P100[4]  ^  RTX[1]  ^  T4[1]  ^  T4[4]  ^  Notes  ^ 
 +|  Mixed  |  |  |  254|  |  |  gpu=1, 01-04  | 
 +|  Mixed  |  |  551|  |  |  546|  gpu=4, 01-04  | 
 +|  Mixed  |  |  |  |  |  650|  gpu=4, 01-08  | 
 +|  Mixed  |  |  |  |  |  733|  gpu=4, 01-16  | 
 + 
 +The T4 is P100's equal in mixed precision performance. Add the wattage factor and you have a favorite. And GPU utilization was outstanding. 
 + 
 +[heme@login1 gromacs-2018]$ ssh node9 ./gpu-info\\ 
 +id,name,temp.gpu,mem.used,mem.free,util.gpu,util.mem\\ 
 +0, Tesla T4, 66, 866 MiB, 14213 MiB, 98 %, 9 %\\ 
 +1, Tesla T4, 67, 866 MiB, 14213 MiB, 98 %, 9 %\\ 
 +2, Tesla T4, 66, 866 MiB, 14213 MiB, 99 %, 9 %\\ 
 +3, Tesla T4, 64, 866 MiB, 14213 MiB, 97 %, 9 %\\
 ==== Scripts ==== ==== Scripts ====
  
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 </code> </code>
 +
 +  * Gromacs
 +
 +<code>
 +
 +#!/bin/bash
 +#SBATCH --nodes=1
 +#SBATCH --nodelist=node9
 +#SBATCH --job-name="T4 dd"
 +#SBATCH --ntasks-per-node=32
 +#SBATCH --gres=gpu:4
 +#SBATCH --exclusive
 +
 +export PATH=$HOME/gromacs-2018/bin:$PATH
 +export LD_LIBRARY_PATH=$HOME/gromacs-2018/lib:$LD_LIBRARY_PATH
 +. $HOME/gromacs-2018/bin/GMXRC.bash
 +rm -f gpu/??/c* gpu/??/e* gpu/??/s* gpu/??/traj* gpu/??/#* gpu/??/m*
 +cd gpu
 +
 +# T4
 +#export CUDA_VISIBLE_DEVICES=0123
 +
 +mpirun -np 8 gmx_mpi mdrun -maxh 1 -gpu_id 0123 \
 +-nsteps 1000000 -multidir 05 06 07 08 \
 +-ntmpi 0 -npme 0 -s topol.tpr -ntomp 0 -pin on -nb gpu
 +
 +</code>
 +
 +
 +
 \\ \\
 **[[cluster:0|Back]]** **[[cluster:0|Back]]**
cluster/182.1565628357.txt.gz · Last modified: 2019/08/12 16:45 by hmeij07

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