The mathlibs-tester scaling performance

depending on the OpenMP MKL-threading

python setup.py --fc=ifort --int64 --mkl=parallel build_ifort_mklpar_i8
python setup.py --fc=ifort --int64 --mkl=sequential build_ifort_mklseq_i8

The DGESV (LAPACK); DGEMM (BLAS) and DNRM2(BLAS) library routines are called.

Run as

/bin/example N i

where N is the size of the matrix, i is the print level (recommended 1).

The lxir071.gsi.de interactive server

Intel(R) Xeon(R) CPU L5506 @ 2.13GHz; 8 CPU

export MKL_NUM_THREADS=#
export MKL_DYNAMIC=false

/bin/example 3000 1

#	time
seq	16.497
1	16.141
2	8.485
4	4.650
8	3.397

The hpcc.umb.sk SIVVP cluster

12 Intel CPU per node

export MKL_NUM_THREADS=#
export MKL_DYNAMIC=false

/bin/example 7000 1

#	time
seq	127.839
2	66.642
4	35.038
8	18.428
12	13.861