[gmx-users] GROMACS performance issues on POWER9/V100 node

Kevin Boyd kevin.boyd at uconn.edu
Fri Apr 24 03:09:14 CEST 2020


Hi,

Can you post the full log for the Intel system? I typically find the real
cycle and time accounting section a better place to start debugging
performance issues.

A couple quick notes, but need a side-by-side comparison for more useful
analysis, and these points may apply to both systems so may not be your
root cause:
* At first glance, your Power system spends 1/3 of its time in constraint
calculation, which is unusual. This can be reduced 2 ways - first, by
adding more CPU cores. It doesn't make a ton of sense to benchmark on one
core if your applications will use more. Second, if you upgrade to Gromacs
2020 you can probably put the constraint calculation on the GPU with
-update GPU.
* The Power system log has this line:
https://github.com/jdh4/running_gromacs/blob/master/03_benchmarks/md.log#L304
indicating
that threads perhaps were not actually pinned. Try adding -pinoffset 0 (or
some other core) to specify where you want the process pinned.

Kevin

On Thu, Apr 23, 2020 at 9:40 AM Jonathan D. Halverson <
halverson at princeton.edu> wrote:

> *Message sent from a system outside of UConn.*
>
>
> We are finding that GROMACS (2018.x, 2019.x, 2020.x) performs worse on an
> IBM POWER9/V100 node versus an Intel Broadwell/P100. Both are running RHEL
> 7.7 and Slurm 19.05.5. We have no concerns about GROMACS on our Intel
> nodes. Everything below is about of the POWER9/V100 node.
>
> We ran the RNASE benchmark with 2019.6 with PME and cubic box using 1
> CPU-core and 1 GPU (
> ftp://ftp.gromacs.org/pub/benchmarks/rnase_bench_systems.tar.gz) and
> found that the Broadwell/P100 gives 144 ns/day while POWER9/V100 gives 102
> ns/day. The difference in performance is roughly the same for the larger
> ADH benchmark and when different numbers of CPU-cores are used. GROMACS is
> always underperforming on our POWER9/V100 nodes. We have pinning turned on
> (see Slurm script at bottom).
>
> Below is our build procedure on the POWER9/V100 node:
>
> version_gmx=2019.6
> wget ftp://ftp.gromacs.org/pub/gromacs/gromacs-${version_gmx}.tar.gz
> tar zxvf gromacs-${version_gmx}.tar.gz
> cd gromacs-${version_gmx}
> mkdir build && cd build
>
> module purge
> module load rh/devtoolset/7
> module load cudatoolkit/10.2
>
> OPTFLAGS="-Ofast -mcpu=power9 -mtune=power9 -mvsx -DNDEBUG"
>
> cmake3 .. -DCMAKE_BUILD_TYPE=Release \
> -DCMAKE_C_COMPILER=gcc -DCMAKE_C_FLAGS_RELEASE="$OPTFLAGS" \
> -DCMAKE_CXX_COMPILER=g++ -DCMAKE_CXX_FLAGS_RELEASE="$OPTFLAGS" \
> -DGMX_BUILD_MDRUN_ONLY=OFF -DGMX_MPI=OFF -DGMX_OPENMP=ON \
> -DGMX_SIMD=IBM_VSX -DGMX_DOUBLE=OFF \
> -DGMX_BUILD_OWN_FFTW=ON \
> -DGMX_GPU=ON -DGMX_CUDA_TARGET_SM=70 \
> -DGMX_OPENMP_MAX_THREADS=128 \
> -DCMAKE_INSTALL_PREFIX=$HOME/.local \
> -DGMX_COOL_QUOTES=OFF -DREGRESSIONTEST_DOWNLOAD=ON
>
> make -j 10
> make check
> make install
>
> 45 of the 46 tests pass with the exception being HardwareUnitTests. There
> are several posts about this and apparently it is not a concern. The full
> build log is here:
> https://github.com/jdh4/running_gromacs/blob/master/03_benchmarks/build.log
>
>
>
> Here is more info about our POWER9/V100 node:
>
> $ lscpu
> Architecture:          ppc64le
> Byte Order:            Little Endian
> CPU(s):                128
> On-line CPU(s) list:   0-127
> Thread(s) per core:    4
> Core(s) per socket:    16
> Socket(s):             2
> NUMA node(s):          6
> Model:                 2.3 (pvr 004e 1203)
> Model name:            POWER9, altivec supported
> CPU max MHz:           3800.0000
> CPU min MHz:           2300.0000
>
> You see that we have 4 hardware threads per physical core. If we use 4
> hardware threads on the RNASE benchmark instead of 1 the performance goes
> to 119 ns/day which is still about 20% less than the Broadwell/P100 value.
> When using multiple CPU-cores on the POWER9/V100 there is significant
> variation in the execution time of the code.
>
> There are four GPUs per POWER9/V100 node:
>
> $ nvidia-smi -q
> Driver Version                      : 440.33.01
> CUDA Version                        : 10.2
> GPU 00000004:04:00.0
>     Product Name                    : Tesla V100-SXM2-32GB
>
> The GPUs have been shown to perform as expected on other applications.
>
>
>
>
> The following lines are found in md.log for the POWER9/V100 run:
>
> Overriding thread affinity set outside gmx mdrun
> Pinning threads with an auto-selected logical core stride of 128
> NOTE: Thread affinity was not set.
>
> The full md.log is available here:
> https://github.com/jdh4/running_gromacs/blob/master/03_benchmarks/md.log
>
>
>
>
> Below are the MegaFlops Accounting for the POWER9/V100 versus
> Broadwell/P100:
>
> ================ IBM POWER9 WITH NVIDIA V100 ================
> Computing:                               M-Number         M-Flops  % Flops
>
> -----------------------------------------------------------------------------
>  Pair Search distance check             297.763872        2679.875     0.0
>  NxN Ewald Elec. + LJ [F]            244214.215808    16118138.243    98.0
>  NxN Ewald Elec. + LJ [V&F]            2483.565760      265741.536     1.6
>  1,4 nonbonded interactions              53.415341        4807.381     0.0
>  Shift-X                                  3.029040          18.174     0.0
>  Angles                                  37.043704        6223.342     0.0
>  Propers                                 55.825582       12784.058     0.1
>  Impropers                                4.220422         877.848     0.0
>  Virial                                   2.432585          43.787     0.0
>  Stop-CM                                  2.452080          24.521     0.0
>  Calc-Ekin                               48.128080        1299.458     0.0
>  Lincs                                   20.536159        1232.170     0.0
>  Lincs-Mat                              444.613344        1778.453     0.0
>  Constraint-V                           261.192228        2089.538     0.0
>  Constraint-Vir                           2.430161          58.324     0.0
>  Settle                                  73.382008       23702.389     0.1
>
> -----------------------------------------------------------------------------
>  Total                                                16441499.096   100.0
>
> -----------------------------------------------------------------------------
>
>
> ================ INTEL BROADWELL WITH NVIDIA P100 ================
>  Computing:                               M-Number         M-Flops  % Flops
>
> -----------------------------------------------------------------------------
>  Pair Search distance check             271.334272        2442.008     0.0
>  NxN Ewald Elec. + LJ [F]            191599.850112    12645590.107    98.0
>  NxN Ewald Elec. + LJ [V&F]            1946.866432      208314.708     1.6
>  1,4 nonbonded interactions              53.415341        4807.381     0.0
>  Shift-X                                  3.029040          18.174     0.0
>  Bonds                                   10.541054         621.922     0.0
>  Angles                                  37.043704        6223.342     0.0
>  Propers                                 55.825582       12784.058     0.1
>  Impropers                                4.220422         877.848     0.0
>  Virial                                   2.432585          43.787     0.0
>  Stop-CM                                  2.452080          24.521     0.0
>  Calc-Ekin                               48.128080        1299.458     0.0
>  Lincs                                    9.992997         599.580     0.0
>  Lincs-Mat                               50.775228         203.101     0.0
>  Constraint-V                           240.108012        1920.864     0.0
>  Constraint-Vir                           2.323707          55.769     0.0
>  Settle                                  73.382008       23702.389     0.2
>
> -----------------------------------------------------------------------------
>  Total                                                12909529.017   100.0
>
> -----------------------------------------------------------------------------
>
> Some of the rows are identical between the two tables above. The largest
> difference
> is observed for the "NxN Ewald Elec. + LJ [F]" row.
>
>
>
> Here is our Slurm script:
>
> #!/bin/bash
> #SBATCH --job-name=gmx           # create a short name for your job
> #SBATCH --nodes=1                # node count
> #SBATCH --ntasks=1               # total number of tasks across all nodes
> #SBATCH --cpus-per-task=1        # cpu-cores per task (>1 if
> multi-threaded tasks)
> #SBATCH --mem=4G                 # memory per node (4G per cpu-core is
> default)
> #SBATCH --time=00:10:00          # total run time limit (HH:MM:SS)
> #SBATCH --gres=gpu:1             # number of gpus per node
>
> module purge
> module load cudatoolkit/10.2
>
> BCH=../rnase_cubic
> gmx grompp -f $BCH/pme_verlet.mdp -c $BCH/conf.gro -p $BCH/topol.top -o
> bench.tpr
> gmx mdrun -pin on -ntmpi $SLURM_NTASKS -ntomp $SLURM_CPUS_PER_TASK -s
> bench.tpr
>
>
>
> How do we get optimal performance out of GROMACS on our POWER9/V100 nodes?
>
> Jon
> --
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