People say that GCC (GNU Compiler Collection) cannot generate effective code compared to other proprietary compilers. Is it a myth or reality?
MKL VSL example for grouppooledcovariance (vsldgrouppooledcovariance.f) failed with PGI threading layer.
Grouppooledcovariance example crashs with segmentation fault with PGI threading layer on all platforms due to error in PGI support of OpenMP order clause.
Some ARPACK users have reported stability issues after upgrading to the Intel® Math Kernel Library (Intel® MKL
“Why Should I Update GCC x86 Compiler?” or “GCC Compiler Performance on Intel® Atom™ from Version to Version”
I’ll try to figure out what is new for Intel® Atom™ architecture in new versions of GCC and how this affects performance and code size on the well-known EEMBC CoreMark* benchmark:
Operating System: Ubuntu* 12.04, Ubuntu 13.10
The general matrix-matrix multiplication (GEMM) is a fundamental operation in most scientific, engineering, and data applications. There is an everlasting desire to make this operation run faster.
Intel MKL 11.3 has introduced Intel TBB support.
There are two listed below limitations with Intel® Math Kernel Library (Intel® MKL) 11.3 Update 3 which were discovered recently.