...

#SBATCH --nodes=1
#SBATCH --partition=cpu-clx:testgenoa
./hello.bin

#SBATCH --nodes=1
#SBATCH --partition=cpu-clx:testgenoa
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=96
./hello.bin

...

#SBATCH --nodes=1
#SBATCH --partition=cpu-clx:testgenoa
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=48
./hello.bin

...

#SBATCH --nodes=2
#SBATCH --partition=cpu-clx:testgenoa
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

...

#SBATCH --nodes=2
#SBATCH --partition=standard96:testcpu-genoa
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:

-xCORE-AVX512 -qopt-zmm-usage=high

However, high ZMM usage is not recommended in all cases (read moreImage Removed).

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.

...