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Code execution

For examples for code execution, please visit Slurm partition CPU CLX.

Code compilation

Intel oneAPI compiler

Codeblock
titleSerial icccode execution
collapsetrue
module load intel
iccicx -o hello.bin hello.c
ifortifx -o hello.bin hello.f90
icpcicpx -o hello.bin hello.cpp


Codeblock
titleOpenMP iccthreaded code execution
collapsetrue
module load intel
iccicx -qopenmpfopenmp -o hello.bin hello.c
ifortifx -qopenmpfopenmp -o hello.bin hello.f90 
icpcicpx -qopenmpfopenmp -o hello.bin hello.cpp

...

GNU compiler

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


Codeblock
titleOpenMP gccthreaded code execution
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

To execute your code you need to

  1. have a binary, which is the result of code compilation,
  2. create a slurm job script,
  3. submit the slurm jobs script.

...

titleJob submission
collapsetrue

...

Slurm job script

The examples for slurm job scripts, e.g. myjobscipt.slurm, that cover the setup

...

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

...

Compiler flags

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

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

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

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

-march=skylake-avx512cascadelake -mprefer-vector-width=512

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.

Check out the link below Intel's link line advisor to see what libraries are recommended for a particular use case. https://software.intel.com/en-us/articles/intel-mkl-link-line-advisor/Image Removed