...

Website: https://www.openmx-square.org/index.html

Build

<how to build and run the application>After extracting the files from the source3.962.tar.gz tarball, first create a directory called work and then go into the source3.962 directory. Edit the makefile for the compilers and MPI on the system you will be using. For example, on the HPC-AI Advisory Council’s Rome cluster, using Intel 2023.2 compilers, Intel MKL, and HPC-X 2.19, the following shows the differences between the modified makefile and the original one:

[gerardo@login02 source3.962]$ diff makefile makefile_orig 
9,13c9,12
< ## MKLROOT = /opt/intel/mkl
< CC = mpicc -O3 -march=core-avx2 -ip -no-prec-div -qopenmp -diag-disable=10441 -I${MKLROOT}/include/fftw
< FC = mpif90 -O3 -march=core-avx2 -ip -no-prec-div -qopenmp
< ## LIB= -L${MKLROOT}/lib/intel64 -lmkl_scalapack_lp64 -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -lmkl_blacs_openmpi_lp64 -lmpi_usempif08 -lmpi_usempi_ignore_tkr -lmpi_mpifh -lifcore -liomp5 -lpthread -lm -ldl
< LIB= -L${MKLROOT}/lib/intel64 -lmkl_scalapack_lp64 -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -lmkl_blacs_openmpi_lp64
---
> MKLROOT = /opt/intel/mkl
> CC = mpicc -O3 -xHOST -ip -no-prec-div -qopenmp -I/opt/intel/mkl/include/fftw/
> FC = mpif90 -O3 -xHOST -ip -no-prec-div -qopenmp
> LIB= -L${MKLROOT}/lib/intel64 -lmkl_scalapack_lp64 -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -lmkl_blacs_openmpi_lp64 -lmpi_usempif08 -lmpi_usempi_ignore_tkr -lmpi_mpifh -lifcore -liomp5 -lpthread -lm -ldl
250,251c249
<       $(FC) $(OBJS) $(LIB) -lm -nofor-main -o openmx
<       ## $(CC) $(OBJS) $(LIB) -lm -o openmx
---
>       $(CC) $(OBJS) $(LIB) -lm -o openmx

To build, just execute make install. If everything goes well, there will be an executable called openmx
in the ../work directory you created earlier.

Tasks and Submissions

You can practice building and running with a tiny input, Methane, below.

1. Run the application on 4 CPU nodes with the NVC input and submit the results in the team’s folder with the NVC input. Check different OpenMP threads . Try varying the number of OpenMP threads per MPI rank for your optimal run.

2. Run MPI Profiler to profile the application, which 3 . Which three MPI calls are mostly used? present Include your work results in the team's interview ppt slides.

3. Visualize the results, create a short video that demonstrate the given input via Paraview ParaView or any other suitable tool. Show Include it on in the team’s interview ppt slides. If you use have an X (Twitter) account, please “tag” tag the video/photo with your team name , and share and hashtag the hashtags “#ISC25 #ISC25_SCC” before prior to the team interview.