Compiling on supercomputers

Compiling on TACC

Use the GNU compilers and MKL for the easiest compilation on TACC Stampede. The following commands may be used to invoke cmake (assuming bash shell):

#Select gcc as the compiler:
module load gcc/4.7.1
module load mkl gsl cuda cmake fftw3

#Configure:
CC=gcc CXX=g++ cmake \
   -D EnableCUDA=yes \
   -D EnableMKL=yes \
   -D ForceFFTW=yes \
   -D MKL_PATH="$TACC_MKL_DIR" \
   -D FFTW3_PATH="$TACC_FFTW3_DIR" \
   -D GSL_PATH="$TACC_GSL_DIR" \
   ../jdftx-VERSION/jdftx

make -j12

Make on the login nodes (as shown above) or on the gpu queue if you loaded cuda; it should work on any machine otherwise.

Compiling on NERSC

Use the gnu compiler and MKL to compile JDFTx on NERSC edison/cori. The following commands may be used to invoke cmake (assuming bash shell):

#Select the right compiler and load necessary modules
module swap PrgEnv-intel PrgEnv-gnu
module load gcc cmake gsl cray-fftw
module unload darshan
export CRAYPE_LINK_TYPE="dynamic"

#From inside your build directory
#(assuming relative paths as in the generic instructions above)
CC="cc -dynamic -lmpich" CXX="CC -dynamic -lmpich" cmake \
    -D EnableProfiling=yes \
    -D EnableMKL=yes \
    -D ForceFFTW=yes \
    -D ThreadedBLAS=no \
    -D GSL_PATH=${GSL_DIR} \
    -D FFTW3_PATH=${FFTW_DIR} \
    -D CMAKE_INCLUDE_PATH=${FFTW_INC} \
    ../jdftx-VERSION/jdftx
make -j12

The optional ThreadedBLAS=no line above uses single-threaded MKL with threads managed by JDFTx instead. This slightly reduces performance (around 5%) compared to using MKL threads, but MKL threads frequently lead to a crash when trying to create pthreads elsewhere in JDFTx on NERSC.