[CP2K-user] [CP2K:17944] Re: Errors building CP2K 2022.2 for GPU Inbox

Ole Schütt ole.schuett at cp2k.org
Thu Oct 27 13:11:11 UTC 2022
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Hi Luis,

> Could the order of the CUDA DFLAGS elements be relevant?

No, the order of the DFLAGS does not matter. 

> /home/cp2k-2022.2/src/pw/gpu/pw_gpu_kernels.h(22): error: identifier 
"offloadStream_t" is undefined

This is really strange!

The "offloadStream_t" is defined here: 
https://github.com/cp2k/cp2k/blob/support/v2022.2/src/offload/offload_runtime.h#L27
... which "pw_gpu_kernels.h" includes 
here: https://github.com/cp2k/cp2k/blob/support/v2022.2/src/pw/gpu/pw_gpu_kernels.h#L11

I'm afraid you'll have to do some digging on your local machine to get to 
the bottom of this.

-Ole

On Wednesday, October 26, 2022 at 3:23:56 PM UTC+2 LC wrote:

> Thanks Ole,
>
> I've replaced my DFLAGS  with the new ones:
>
>  -D__MKL -D__FFTW3 -D__LIBXSMM  -D__LIBINT -D__parallel -D__SCALAPACK 
> -D__HAS_ISO_C_BINDING -D__DBCSR_ACC -D__OFFLOAD_CUDA -D__OFFLOAD_PROFILING 
> -D__HAS_PATCHED_CUFFT_70 -D__COSMA -D__ELPA_NVIDIA_GPU -D__LIBVORI 
> -D__SPGLIB
>
> Unfortunately, I am still getting the same error. Could the order of the 
> CUDA DFLAGS elements be relevant?
>
> Regards
>
>
> On 26/10/2022 14:03, Ole Schütt wrote:
>
> Hi Luis,
>
> the flags for GPU support have recently changed a bit:
>
>   
> https://github.com/cp2k/cp2k/blob/master/INSTALL.md#2i-cuda-optional-improved-performance-on-gpu-systems
>
>  Try adding -D__OFFLOAD_CUDA
>
> -Ole
>
> On Wednesday, October 26, 2022 at 2:35:08 PM UTC+2 LC wrote:
>
>> Hello,
>>
>> I am trying to build CP2K 2022.2 for NVIDIA GPUs. I've built  ELPA with 
>> GPU support (no OpenMP, yes MPI), and COSMA 2.5 with GPU support too. The 
>> error I am getting is as follows:
>>
>> mpifort -c -D__MKL -D__FFTW3 -D__LIBXSMM  -D__LIBINT -D__parallel 
>> -D__SCALAPACK -D__HAS_ISO_C_BINDING -D__ACC -D__DBCSR_ACC -D__PW_CUDA 
>> -D__GRID_CUDA -D__OFFLOAD_PROFILING -D__HAS_PATCHED_CUFFT_70 -D__COSMA 
>> -D__ELPA_NVIDIA_GPU  -D__LIBVORI -D__SPGLIB -O3 -fopenmp -ffree-form 
>> -ffree-line-length-none -ftree-vectorize -funroll-loops -std=f2008 
>> -I/opt/intel/compilers_and_libraries_2019.5.281/linux/mkl/include 
>>  -I/home/COSMA/include -I/home/libxsmm-1.17.0/include   
>> -I/home/elpa-2021.11.002/include/elpa-2021.11.002/modules 
>> -I/home/elpa-2021.11.002/include/elpa-2021.11.002/elpa 
>> -I/home/elpa-2021.11.002/include/elpa-2021.11.002/src/helpers 
>> -I/home/fftw-3.3.10/include -I/home/libint-v2.6.0-cp2k-lmax-4/include 
>> -I/cuda/cuda-11.2/include -m64 
>> -I/opt/intel/compilers_and_libraries_2019.5.281/linux/mkl/include 
>> -D__COMPILE_ARCH="\"nvidiaGPU\""  -D__COMPILE_REVISION="\"git:a95ec40\"" 
>> -D__DATA_DIR="\"/home/cp2k-2022.2/data\"" 
>> -D__SHORT_FILE__="\"xc/xc_input_constants.F\"" 
>> -I'/home/cp2k-2022.2/src/xc/' 
>> -I'/home/cp2k-2022.2/obj/nvidiaGPU/psmp/exts/dbcsr' xc_input_constants.F90 
>>
>> /home/cp2k-2022.2/tools/build_utils/fypp -n 
>> /home/cp2k-2022.2/src/shg_int/constants_operator.F constants_operator.F90
>> cmp: /home/cp2k-2022.2/obj/git-ref: No such file or directory
>> /home/cp2k-2022.2/src/pw/gpu/pw_gpu_kernels.h(22): error: identifier 
>> "offloadStream_t" is undefined
>>
>> and here you can see my arch file:
>>
>>
>> NVCC     = ${CUDA_HOME}/bin/nvcc
>> GPUVER   = V100
>>
>> CXX      = mpicxx
>> CC       = mpicc
>> FC       = mpifort
>> LD       = mpifort
>> AR       = ar -r
>>
>> OFFLOAD_CC = nvcc
>> OFFLOAD_FLAGS = -O3 -g -w --std=c++11
>>
>> OPTFLAGS += -fopenmp -O3 -march=native
>>
>> DFLAGS   += -D__MKL -D__FFTW3 -D__LIBXSMM  -D__LIBINT \
>>   -D__parallel -D__SCALAPACK -D__HAS_ISO_C_BINDING
>>   
>> DFLAGS += -D__ACC -D__DBCSR_ACC -D__PW_CUDA -D__GRID_CUDA 
>> -D__OFFLOAD_PROFILING
>> DFLAGS += -D__HAS_PATCHED_CUFFT_70 -D__COSMA -D__ELPA_NVIDIA_GPU 
>>
>> DFLAGS+= -D__LIBVORI -D__SPGLIB
>>
>> # C++ flags
>> CXXFLAGS = -O3 $(OPTFLAGS) -g -I${CUDA_HOME}/include -std=c++11
>>
>> # NVIDIA 
>> NVFLAGS  = $(DFLAGS) $(OPTFLAGS) -g -O3 -arch sm_70 -Xcompiler='-fopenmp' 
>> --std=c++11
>>
>> # Fortran flags
>> FCFLAGS  = $(DFLAGS) -O3 -fopenmp -ffree-form -ffree-line-length-none
>> FCFLAGS    += -ftree-vectorize -funroll-loops -std=f2008
>> INC_FLAGS    = -I${MKLROOT}/include 
>> INC_FLAGS    += -I$(COSMA)/include
>> INC_FLAGS    += -I$(LIBXSMM)/include  
>> INC_FLAGS    += -I$(INCELPA)/modules -I$(INCELPA)/elpa 
>> -I$(INCELPA)/src/helpers
>> INC_FLAGS    += -I$(LIBFFTW3)/include
>> INC_FLAGS    += -I$(LIBINT)/include
>> INC_FLAGS    += -I${CUDA_HOME}/include
>> INC_FLAGS    += -m64 -I${MKLROOT}/include
>>
>> # C++ flags
>> CXXFLAGS += $(INC_FLAGS)
>>
>> FCFLAGS +=  $(INC_FLAGS)
>>
>> # C flags
>> CFLAGS   = $(DFLAGS) $(OPTFLAGS) $(INC_FLAGS)
>>
>> # Libraries
>> LDFLAGS  = $(FCFLAGS) 
>> LDFLAGS_C = $(FCFLAGS)
>>
>> # ELPA libs
>> LIBS     = $(LIBELPA)/lib/libelpa.a
>> # Libvori lib
>> LIBS     += $(LIBVORI)/lib/libvori.a
>> # LIBXSMM libs
>> LIBS    += -L$(LIBXSMM)/lib -lxsmmf -lxsmm -lxsmmext  
>> # LIBINT libs
>> LIBS    += -L$(LIBINT)/lib -lint2 -lstdc++
>> # FFTW libs
>> LIBS    += -L$(LIBFFTW3)/lib -lfftw3 -lfftw3_threads
>> #SPGLIB
>> LIBS    += -L$(LIBSPG)/lib64 -lsymspg
>> #LIBXC
>> LIBS += -L$(LIBXC)/lib -lxcf03 -lxc
>>
>> # Scalapack libs
>> LIBS    += -L/usr/lib64
>>
>> LIBS    += -L$(MKLROOT)/lib/intel64 -Wl,--start-group 
>> -lmkl_scalapack_lp64 -lmkl_gf_lp64 -lmkl_sequential -lmkl_core -l
>> mkl_blacs_openmpi_lp64 -Wl,--end-group -lpthread -lz -ldl
>>   
>> #COSMA
>> LIBS    += -L$(COSMA_LIB)/ -lcosma_prefixed_pxgemm -lcosma 
>> -lcosta_prefixed_scalapack -lcosta
>>
>> #CUDA
>> LIBS   += -L${CUDA_HOME}/lib64 -lstdc++ -lcudart -lnvrtc -lcuda -lcufft 
>> -lcublas -lnvToolsExt
>>
>> # Required due to memory leak that occurs if high optimisations are used
>> mp2_optimize_ri_basis.o: mp2_optimize_ri_basis.F
>> $(FC) -c $(subst O2,O0,$(FCFLAGS)) $< 
>>
>> Could anyone help me with this please?
>>
>> Regards
>> LC
>>
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