Hey guys,
Anybody running GROMACS on AWS ?
I have a strong IT background , but zero understanding of GROMACS or OpenMPI. (
even less using sge on AWS ),
Just trying to help some PHD Folks with their work.
When I run gromacs using Thread-mpi on a single, very large node on AWS things
work fairly fast.
However, when I switch from thread-mpi to OpenMPI even though everything's
detected properly, the performance is horrible.
This is what I am submitting to sge:
ubuntu@ip-10-10-5-81:/shared/charmm-gui/gromacs$ cat sge.sh
#!/bin/bash
#
#$ -cwd
#$ -j y
#$ -S /bin/bash
#$ -e out.err
#$ -o out.out
#$ -pe mpi 256
cd /shared/charmm-gui/gromacs
touch start.txt
/bin/bash /shared/charmm-gui/gromacs/run_eq.bash
touch end.txt
and this is my test script , provided by one of the Doctors:
ubuntu@ip-10-10-5-81:/shared/charmm-gui/gromacs$ cat run_eq.bash
#!/bin/bash
export GMXMPI="/usr/bin/mpirun --mca btl ^openib
/shared/gromacs/5.1.5/bin/gmx_mpi"
export MDRUN="mdrun -ntomp 2 -npme 32"
export GMX="/shared/gromacs/5.1.5/bin/gmx_mpi"
for comm in min eq; do
if [ $comm == min ]; then
echo ${comm}
$GMX grompp -f step6.0_minimization.mdp -o step6.0_minimization.tpr -c
step5_charmm2gmx.pdb -p topol.top
$GMXMPI $MDRUN -deffnm step6.0_minimization
fi
if [ $comm == eq ]; then
for step in `seq 1 6`;do
echo $step
if [ $step -eq 1 ]; then
echo ${step}
$GMX grompp -f step6.${step}_equilibration.mdp -o
step6.${step}_equilibration.tpr -c step6.0_minimization.gro -r
step5_charmm2gmx.pdb -n index.ndx -p topol.top
$GMXMPI $MDRUN -deffnm step6.${step}_equilibration
fi
if [ $step -gt 1 ]; then
old=`expr $step - 1`
echo $old
$GMX grompp -f step6.${step}_equilibration.mdp -o
step6.${step}_equilibration.tpr -c step6.${old}_equilibration.gro -r
step5_charmm2gmx.pdb -n index.ndx -p topol.top
$GMXMPI $MDRUN -deffnm step6.${step}_equilibration
fi
done
fi
done
during the output, I see this , and I get really excited, expecting blazing
speeds and yet, it's much worse than a single node:
Command line:
gmx_mpi mdrun -ntomp 2 -npme 32 -deffnm step6.0_minimization
Back Off! I just backed up step6.0_minimization.log to
./#step6.0_minimization.log.6#
Running on 4 nodes with total 128 cores, 256 logical cores, 32 compatible GPUs
Cores per node: 32
Logical cores per node: 64
Compatible GPUs per node: 8
All nodes have identical type(s) of GPUs
Hardware detected on host ip-10-10-5-89 (the node of MPI rank 0):
CPU info:
Vendor: GenuineIntel
Brand: Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz
SIMD instructions most likely to fit this hardware: AVX2_256
SIMD instructions selected at GROMACS compile time: AVX2_256
GPU info:
Number of GPUs detected: 8
#0: NVIDIA Tesla V100-SXM2-16GB, compute cap.: 7.0, ECC: yes, stat:
compatible
#1: NVIDIA Tesla V100-SXM2-16GB, compute cap.: 7.0, ECC: yes, stat:
compatible
#2: NVIDIA Tesla V100-SXM2-16GB, compute cap.: 7.0, ECC: yes, stat:
compatible
#3: NVIDIA Tesla V100-SXM2-16GB, compute cap.: 7.0, ECC: yes, stat:
compatible
#4: NVIDIA Tesla V100-SXM2-16GB, compute cap.: 7.0, ECC: yes, stat:
compatible
#5: NVIDIA Tesla V100-SXM2-16GB, compute cap.: 7.0, ECC: yes, stat:
compatible
#6: NVIDIA Tesla V100-SXM2-16GB, compute cap.: 7.0, ECC: yes, stat:
compatible
#7: NVIDIA Tesla V100-SXM2-16GB, compute cap.: 7.0, ECC: yes, stat:
compatible
Reading file step6.0_minimization.tpr, VERSION 5.1.5 (single precision)
Using 256 MPI processes
Using 2 OpenMP threads per MPI process
On host ip-10-10-5-89 8 compatible GPUs are present, with IDs 0,1,2,3,4,5,6,7
On host ip-10-10-5-89 8 GPUs auto-selected for this run.
Mapping of GPU IDs to the 56 PP ranks in this node:
0,0,0,0,0,0,0,1,1,1,1,1,1,1,2,2,2,2,2,2,2,3,3,3,3,3,3,3,4,4,4,4,4,4,4,5,5,5,5,5,5,5,6,6,6,6,6,6,6,7,7,7,7,7,7,7
Any suggestions? Greatly appreciate the help.
Carlos J. Rivas
Senior AWS Solutions Architect - Migration Specialist
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