[CP2K-user] [CP2K:20303] Re: Running cp2k on GPU

'Hemanth Haridas' via cp2k cp2k at googlegroups.com
Tue Jun 11 14:37:29 UTC 2024
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The script that I used for submitting is reproduced below

#!/bin/bash

#SBATCH --job-name=LiCl                 ### Job Name

#SBATCH --output=cp2k.out               ### File in which to store job 
output

#SBATCH --error=cp2k.err                ### File in which to store job 
error messages

#SBATCH --time=3-00:00:00               ### Wall clock time limit in 
Days-HH:MM:SS              

#SBATCH --ntasks=64

#SBATCH --gres=gpu:1

#SBATCH --cpus-per-task=1


module load gcc cuda/11.8.0 openmpi/4.1.6-gpu intel-oneapi-mkl/2022.0.2


source /cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/setup


export* OMP_NUM_THREADS=*$SLURM_NTASKS


mpirun -np 1 /cp2k_plumed_gpu/cp2k-2024.1/exe/local_cuda/cp2k.psmp -i
 colvars.inp -o colvars.out


We do not have a version of cp2k installed cluster-wide meaning that I do 
not have a script that I can compare with.
On Tuesday, June 11, 2024 at 5:07:07 AM UTC-6 Johann Pototschnig wrote:

> Which GPU bindings did you end up using?
>
> Did you compare to submission scripts for your cluster for which the GPU 
> is used?
>
>
> On Monday, June 10, 2024 at 6:31:45 PM UTC+2 Hemanth Haridas wrote:
>
>> I tried running cp2k as described in the previous email, but the code 
>> still does not run on the gpu, and the GPU usage is still zero.
>>
>> Sincererly,
>> Hemanth
>>
>> On Friday, June 7, 2024 at 11:02:42 AM UTC-6 Johann Pototschnig wrote:
>>
>>> For cuda it is rather:
>>> https://github.com/tom-papatheodore/hello_jobstep
>>>
>>> On Friday, June 7, 2024 at 6:52:33 PM UTC+2 Johann Pototschnig wrote:
>>>
>>>> It links to cuda, there should be no problem, but you are missing the 
>>>> mpirun / srun:
>>>>
>>>> mpirun -n 1 -x OMP_NUM_THREADS=$...  /cp2k_plumed_gpu/cp2k-2024.1/exe/local_cuda/cp2k.psmp 
>>>> -i colvars.inp -o colvars.out
>>>>
>>>>
>>>> depending on your system there might be additional options for 
>>>> mpirun/srun necessary. 
>>>>
>>>> The following program can help to figure out bindings:
>>>> https://code.ornl.gov/olcf/hello_jobstep
>>>>
>>>> On Friday, June 7, 2024 at 5:18:47 PM UTC+2 Hemanth Haridas wrote:
>>>>
>>>>> CC          = 
>>>>> /gcc-8.5.0/openmpi-4.1.6-chhfokbbf3fbb2t4uo7ns4ukaripskzj/bin/mpicc
>>>>>
>>>>> CXX         = 
>>>>> /gcc-8.5.0/openmpi-4.1.6-chhfokbbf3fbb2t4uo7ns4ukaripskzj/bin/mpic++
>>>>>
>>>>> AR          = ar -r
>>>>>
>>>>> FC          = 
>>>>> /gcc-8.5.0/openmpi-4.1.6-chhfokbbf3fbb2t4uo7ns4ukaripskzj/bin/mpifort
>>>>>
>>>>> LD          = 
>>>>> /gcc-8.5.0/openmpi-4.1.6-chhfokbbf3fbb2t4uo7ns4ukaripskzj/bin/mpifort
>>>>>
>>>>> #
>>>>>
>>>>> DFLAGS      = -D__OFFLOAD_CUDA -D__DBCSR_ACC  -D__LIBXSMM  
>>>>> -D__parallel -D__MKL -D__FFTW3  -D__SCALAPACK -D__LIBINT -D__LIBXC 
>>>>> -D__LIBGRPP -D__GSL -D__PLUMED2 -D__SPGLIB  -D__OFFLOAD_GEMM  -D__SPLA
>>>>>
>>>>> #
>>>>>
>>>>> WFLAGS      = -Werror=aliasing -Werror=ampersand 
>>>>> -Werror=c-binding-type -Werror=intrinsic-shadow -Werror=intrinsics-std 
>>>>> -Werror=line-truncation -Werror=tabs -Werror=target-lifetime 
>>>>> -Werror=underflow -Werror=unused-but-set-variable -Werror=unused-variable 
>>>>> -Werror=unused-dummy-argument -Werror=unused-parameter -Werror=unused-label 
>>>>> -Werror=conversion -Werror=zerotrip -Wno-maybe-uninitialized 
>>>>> -Wuninitialized -Wuse-without-only
>>>>>
>>>>> #
>>>>>
>>>>> FCDEBFLAGS  = -fbacktrace -ffree-form -fimplicit-none -std=f2008
>>>>>
>>>>> CFLAGS      = -fno-omit-frame-pointer -fopenmp -g -mtune=native  -O3 
>>>>> -funroll-loops $(PROFOPT)  
>>>>> -I/gcc-8.5.0/openmpi-4.1.6-chhfokbbf3fbb2t4uo7ns4ukaripskzj/include 
>>>>> -pthread  -m64 
>>>>> -I/gcc-8.5.0/intel-oneapi-mkl-2023.2.0-etwucm5d3s2qu7eiuaaxastbiukj2ori/mkl/2023.2.0/include 
>>>>> -I/gcc-8.5.0/intel-oneapi-mkl-2023.2.0-etwucm5d3s2qu7eiuaaxastbiukj2ori/mkl/2023.2.0/include/fftw 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libint-v2.6.0-cp2k-lmax-5/include' 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libxc-6.2.2/include' 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libgrpp-main-20231215/include' 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libxsmm-1.17/include' 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/gsl-2.7/include' 
>>>>> -I/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/spglib-1.16.2/include 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/SpLA-1.5.5/include/spla' 
>>>>> -std=c11 -Wall -Wextra -Werror -Wno-vla-parameter 
>>>>> -Wno-deprecated-declarations $(DFLAGS) 
>>>>> -I/gcc-8.5.0/cuda-11.8.0-3wlxktsbgw2ui4wvdnsy7w7xyxlkkwju/include
>>>>>
>>>>> FCFLAGS     = -fno-omit-frame-pointer -fopenmp -g -mtune=native  -O3 
>>>>> -funroll-loops $(PROFOPT)  
>>>>> -I/gcc-8.5.0/openmpi-4.1.6-chhfokbbf3fbb2t4uo7ns4ukaripskzj/include 
>>>>> -pthread  -m64 
>>>>> -I/gcc-8.5.0/intel-oneapi-mkl-2023.2.0-etwucm5d3s2qu7eiuaaxastbiukj2ori/mkl/2023.2.0/include 
>>>>> -I/gcc-8.5.0/intel-oneapi-mkl-2023.2.0-etwucm5d3s2qu7eiuaaxastbiukj2ori/mkl/2023.2.0/include/fftw 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libint-v2.6.0-cp2k-lmax-5/include' 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libxc-6.2.2/include' 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libgrpp-main-20231215/include' 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libxsmm-1.17/include' 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/gsl-2.7/include' 
>>>>> -I/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/spglib-1.16.2/include 
>>>>> -I'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/SpLA-1.5.5/include/spla' 
>>>>> $(FCDEBFLAGS) $(WFLAGS) $(DFLAGS)
>>>>>
>>>>> CXXFLAGS    = -O2 -fPIC -fno-omit-frame-pointer -fopenmp -g 
>>>>> -march=native -mtune=native --std=c++14 $(DFLAGS) 
>>>>> -Wno-deprecated-declarations 
>>>>> -I/gcc-8.5.0/cuda-11.8.0-3wlxktsbgw2ui4wvdnsy7w7xyxlkkwju/include
>>>>>
>>>>> #
>>>>>
>>>>> LDFLAGS     =  $(FCFLAGS) -Wl,--enable-new-dtags -pthread 
>>>>> -L/gcc-8.5.0/openmpi-4.1.6-chhfokbbf3fbb2t4uo7ns4ukaripskzj/lib 
>>>>> -L/gcc-8.5.0/ucx-1.14.0-cupo7hrn2exqqwfyatdigeuiiqijaulw/lib -L/uufs/
>>>>> chpc.utah.edu/sys/spack/v019/linux-rocky8-x86_64/gcc-8.5.0/zlib-1.2.13-dcpzngybj4fisn6ojapnels3yfwcxqgk/lib 
>>>>> -Wl,-rpath 
>>>>> -Wl,/gcc-8.5.0/openmpi-4.1.6-chhfokbbf3fbb2t4uo7ns4ukaripskzj/lib 
>>>>> -Wl,-rpath -Wl,/gcc-8.5.0/ucx-1.14.0-cupo7hrn2exqqwfyatdigeuiiqijaulw/lib 
>>>>> -Wl,-rpath -Wl,/gcc-8.5.0/zlib-1.2.13-dcpzngybj4fisn6ojapnels3yfwcxqgk/lib  
>>>>>   
>>>>> -L'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libint-v2.6.0-cp2k-lmax-5/lib' 
>>>>> -L'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libxc-6.2.2/lib' 
>>>>> -Wl,-rpath,'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libxc-6.2.2/lib' 
>>>>> -L'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libgrpp-main-20231215/lib' 
>>>>> -Wl,-rpath,'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libgrpp-main-20231215/lib' 
>>>>> -L'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libxsmm-1.17/lib' 
>>>>> -Wl,-rpath,'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/libxsmm-1.17/lib' 
>>>>> -L'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/gsl-2.7/lib' 
>>>>> -Wl,-rpath,'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/gsl-2.7/lib' 
>>>>> -L'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/plumed-2.9.0/lib' 
>>>>> -Wl,-rpath,'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/plumed-2.9.0/lib' 
>>>>> -L'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/spglib-1.16.2/lib' 
>>>>> -Wl,-rpath,'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/spglib-1.16.2/lib' 
>>>>> -L'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/SpLA-1.5.5/lib/cuda' 
>>>>> -Wl,-rpath,'/cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/SpLA-1.5.5/lib/cuda' 
>>>>> -L'/gcc-8.5.0/cuda-11.8.0-3wlxktsbgw2ui4wvdnsy7w7xyxlkkwju/targets/x86_64-linux/lib' 
>>>>> -Wl,-rpath,'/gcc-8.5.0/cuda-11.8.0-3wlxktsbgw2ui4wvdnsy7w7xyxlkkwju/targets/x86_64-linux/lib' 
>>>>> -L'/usr/lib64' -Wl,-rpath,'/usr/lib64'
>>>>>
>>>>> LDFLAGS_C   =
>>>>>
>>>>> LIBS        = -lspla -lsymspg -l:libplumed.a -ldl -lstdc++ -lz -ldl 
>>>>> -lgsl -lxsmmf -lxsmm -ldl -lpthread -llibgrpp -lxcf03 -lxc -lint2   
>>>>> -lmpi_cxx -lmpi  
>>>>> -L/gcc-8.5.0/intel-oneapi-mkl-2023.2.0-etwucm5d3s2qu7eiuaaxastbiukj2ori/mkl/2023.2.0/lib/intel64 
>>>>> -Wl,-rpath,/gcc-8.5.0/intel-oneapi-mkl-2023.2.0-etwucm5d3s2qu7eiuaaxastbiukj2ori/mkl/2023.2.0/lib/intel64 
>>>>> -lmkl_scalapack_lp64 -Wl,--start-group -lmkl_gf_lp64 -lmkl_sequential 
>>>>> -lmkl_core -lmkl_blacs_openmpi_lp64 -Wl,--end-group -lpthread -lm -ldl 
>>>>> -lstdc++ -lcudart -lnvrtc -lcuda -lcufft -lcublas -lrt
>>>>>
>>>>> #
>>>>>
>>>>> GPUVER        = A100
>>>>>
>>>>> OFFLOAD_CC    = nvcc
>>>>>
>>>>> OFFLOAD_FLAGS = -g -arch sm_80 -O3 -allow-unsupported-compiler 
>>>>> -Xcompiler='-fopenmp -Wall -Wextra -Werror' --std=c++11 $(DFLAGS)
>>>>>
>>>>> OFFLOAD_TARGET = cuda
>>>>>
>>>>> #
>>>>>
>>>>> FYPPFLAGS   = -n --line-marker-format=gfortran5
>>>>> On Friday, June 7, 2024 at 1:51:34 AM UTC-6 Johann Pototschnig wrote:
>>>>>
>>>>>> Can you provide the local_cuda.psmp  file which you find in the arch 
>>>>>> folder?
>>>>>>
>>>>>> On Thursday, June 6, 2024 at 9:10:38 PM UTC+2 Hemanth Haridas wrote:
>>>>>>
>>>>>>> I am trying to run CP2K on a linux cluster with GPU support. I have 
>>>>>>> successfully complied the code with CUDA support. But the utilization of 
>>>>>>> GPU is zero, even though the program is running , meaning that the code is 
>>>>>>> running on cpu cores.
>>>>>>>
>>>>>>> This is the script that I am using to run cp2k 
>>>>>>>
>>>>>>> #!/bin/bash
>>>>>>>
>>>>>>> #SBATCH --job-name=LiCl                 ### Job Name
>>>>>>>
>>>>>>> #SBATCH --output=cp2k.out               ### File in which to store 
>>>>>>> job output
>>>>>>>
>>>>>>> #SBATCH --error=cp2k.err                ### File in which to store 
>>>>>>> job error messages
>>>>>>>
>>>>>>> #SBATCH --time=3-00:00:00               ### Wall clock time limit in 
>>>>>>> Days-HH:MM:SS              
>>>>>>>
>>>>>>> #SBATCH --ntasks=64
>>>>>>>
>>>>>>> #SBATCH --gres=gpu:1
>>>>>>>
>>>>>>> #SBATCH --cpus-per-task=1
>>>>>>>
>>>>>>>
>>>>>>> module load gcc cuda/11.8.0 openmpi/4.1.6-gpu intel-oneapi-mkl/2022.
>>>>>>> 0.2
>>>>>>>
>>>>>>>
>>>>>>> source /cp2k_plumed_gpu/cp2k-2024.1/tools/toolchain/install/setup
>>>>>>>
>>>>>>>
>>>>>>> export* OMP_NUM_THREADS=*$SLURM_NTASKS
>>>>>>>
>>>>>>>
>>>>>>> /cp2k_plumed_gpu/cp2k-2024.1/exe/local_cuda/cp2k.psmp -i 
>>>>>>> colvars.inp -o colvars.out
>>>>>>>
>>>>>>>
>>>>>>> Are there any additional flags that I need to use to run the code on 
>>>>>>> GPUs?
>>>>>>>
>>>>>>

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