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Code compilation

Intel compiler

Codeblock
titleSerial icc
collapsetrue
module load intel
icc -o hello.bin hello.c
ifort -o hello.bin hello.f90
icpc -o hello.bin hello.cpp


Codeblock
titleOpenMP icc
collapsetrue
module load intel
icc -qopenmp -o hello.bin hello.c
ifort -qopenmp -o hello.bin hello.f90 
icpc -qopenmp -o hello.bin hello.cpp

Gnu compiler

Codeblock
titleSerial gcc
collapsetrue
module load gcc
gcc -o hello.bin hello.c
gfortran -o hello.bin hello.f90
g++ -o hello.bin hello.cpp


Codeblock
titleOpenMP gcc
collapsetrue
module load gcc
gcc -fopenmp -o hello.bin hello.c
gfortran -fopenmp -o hello.bin hello.f90
g++ -fopenmp -o hello.bin hello.cpp

Code execution

You can run a single OpenMP code. The examples cover the setup

  • 1 node,
  • 1 OpenMP code running.
Codeblock
titleSerial
collapsetrue
#SBATCH --nodes=1
./hello.bin


Codeblock
titleOpenMP, full node
collapsetrue
#SBATCH --nodes=1
#SBATCH --partition=standard96:test
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=96
./hello.bin


Codeblock
titleOpenMP, half node
collapsetrue
#SBATCH --nodes=1
#SBATCH --partition=standard96:test
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=48
./hello.bin


Codeblock
titleOpenMP, hyperthreading
collapsetrue
#SBATCH --nodes=1
#SBATCH --partition=standard96:test
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=192
./hello.bin

You can run different OpenMP codes at the same time. The examples cover the setup

  • 2 nodes,
  • 4 OpenMP codes run simultaneously.
  • The code is not MPI parallel. mpirun is used to start the codes only.
Codeblock
titleOpenMP simultaneously
collapsetrue
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
module load impi/2019.5
export SLURM_CPU_BIND=none
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=48
mpirun -ppn 2 \
       -np 1 ./code1.bin : -np 1 ./code2.bin : -np 1 ./code3.bin : -np 1 ./code4.bin


Codeblock
titleOpenMP simultaneously hyperthreading
collapsetrue
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
module load impi/2019.5
export SLURM_CPU_BIND=none
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=96
mpirun -ppn 2 \
       -np 1 ./code1.bin

...

 : -np 1 ./code2.bin : -np 1 ./code3.bin : -np 1 ./code4.bin

Intel compiler flags

To make full use of the vectorizing capabilities of the CPUs, AVX512 instructions and the 512bit ZMM registers can be used with the following compile flags with the Intel compilers:

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With GNU compilers (GCC 7.x and later), architecture-specific optimization for Skylake and Cascade Lake CPUs is enabled with

-march=skylake-avx512

Using the Intel MKL

The Intel® Math Kernel Library (Intel® MKL) is designed to run on multiple processors and operating systems. It is also compatible with several compilers and third party libraries, and provides different interfaces to the functionality. To support these different environments, tools, and interfaces Intel MKL provides multiple libraries from which to choose.

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