This is an old version of this page. You can view the most recent version or browse the history.

ELPA installation guide

Below we provide examples of compilation process in on selected systems

Installation on Summit

Notes by Victor Wen-zhe Yu:

Installation instructions

For compilation use interactive session:

bsub -Is -W 0:15 -nnodes 1 -P nph139 $SHELL

Next execute:

module load gcc/7.4.0
module load m4
module load libtool
module load autoconf
module load automake
module load cuda 
module load essl
module load netlib-lapack
module load netlib-scalapack
module load python/3.7.0

git clone https://gitlab.mpcdf.mpg.de/elpa/elpa.git

# go to ELPA distribution directory
cd elpa
./autogen.sh
mkdir build && cd build

../configure FC=mpif90 CC=mpicc FCFLAGS="-O2 -mcpu=power9 -ffree-line-length-none" CFLAGS="-O2 -mcpu=power9" CPP="cpp -E" LDFLAGS="-L${OLCF_NETLIB_SCALAPACK_ROOT}/lib -lscalapack -L${OLCF_ESSL_ROOT}/lib64 -lessl -L${OLCF_NETLIB_LAPACK_ROOT}/lib64 -llapack" --disable-openmp --enable-gpu --with-cuda-path=${OLCF_CUDA_ROOT} --with-GPU-compute-capability=sm_70 --disable-sse-assembly --disable-sse --disable-avx --disable-avx2 --disable-avx512 --enable-c-tests=no --prefix="/ccs/home/gabrielw/proj-shared/share/elpa"

make -j 8

# Before you install lib, check if CUDA support works correctly
jsrun -n 6 -a 1 -c 1 -g 1 ./validate_complex_double_eigenvectors_2stage_default_kernel_gpu_random 1000 1000 16  
jsrun -n 6 -a 1 -c 1 -g 1 ./validate_real_double_eigenvectors_2stage_default_kernel_gpu_random 1000 1000 16

# If tests are ok, install to the final destination
make install

Installation on Piz Daint

# Clone latest version
git clone https://gitlab.mpcdf.mpg.de/elpa/elpa.git

# Load modules
module load daint-gpu
module swap PrgEnv-cray PrgEnv-gnu/6.0.9
module swap gcc gcc/9.3.0
module load cudatoolkit/11.0.2_3.33-7.0.2.1_3.1__g1ba0366
module load craype-accel-nvidia60
module list

./autogen.sh

# go to ELPA distribution directory

mkdir build && cd build

../configure --prefix="/project/pr91/share" FC=ftn CC=cc FCFLAGS="-O2 -ffree-line-length-none" CFLAGS="-O2" -disable-avx512 --disable-openmp --enable-static --enable-gpu --with-cuda-path=${CRAY_CUDATOOLKIT_DIR} --with-GPU-compute-capability=sm_60 --enable-c-tests=no

make 

make install

Installation on Cygnus

module load intel/19.0.5
module load mkl/19.0.5
module load cuda/10.2
module load intmpi/19.0.5

# go to ELPA distribution directory

mkdir build && cd build

../configure --prefix="/work/TDSLDA20/share/elpa" --enable-static CC=mpiicc FC=mpiifort CPP=cpp FCPP=cpp  LIBS="-lmkl_scalapack_lp64 -lmkl_blacs_intelmpi_lp64 -lpthread -lm -ldl -mkl=cluster"  FCFLAGS="-mkl=cluster -O3 -xAVX2" CFLAGS="-mkl=cluster -qopenmp -O3 -xAVX2" --enable-gpu --with-cuda-path=${CUDA_PATH} --with-GPU-compute-capability=sm_60

make 

make install

Installation on Tsubame

module load cuda/10.2.89 
module load intel/19.1.0.166 
module load intel-mpi/19.6.166

# go to ELPA distribution directory
mkdir && cd
git clone https://gitlab.mpcdf.mpg.de/elpa/elpa && ./autogen.sh && cd ..
mkdir build && cd build
../configure --prefix="/gs/hs1/hp190063/share/elpa" --disable-openmp --enable-static CC=mpiicc FC=mpiifort LIBS="-lmkl_scalapack_ilp64 -lmkl_blacs_intelmpi_ilp64 -lpthread -lm -ldl  -DMKL_ILP64 -mkl=cluster"  FCFLAGS="-DMKL_ILP64 -mkl=cluster -O3 -xAVX2" CFLAGS="-DMKL_ILP64 -mkl=cluster -O3 -xAVX2" --enable-gpu --with-cuda-path=${CUDA_PATH} --with-GPU-compute-capability=sm_60

make 

make install