“I don’t know, but it works on my machine!!” Ever said that? Ever heard that? Ever wondered why it happens?
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.
A Matrix Multiplication Routine that Updates Only the Upper or Lower Triangular Part of the Result MatrixBackground
Intel® MKL provides the general purpose BLAS* matrix multiply routines ?GEMM defined as follows:
(This work was done by Vivek Lingegowda during his internship at Intel.)
There is a long discussion talking about the advantages of Procedural Programming vs. the advantages of Object Oriented Programming.
Some ARPACK users have reported stability issues after upgrading to the Intel® Math Kernel Library (Intel® MKL
One of the pitfalls of parallel programming is the need to consider whether your code modifies a memory location in two parallel strands.
“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: