Originally posted by: Robert Enenkel

If your applications call mathematical functions such as sin, cos, exp, log, etc. and you are interested in maximizing performance with minimum effort, here is something that will interest you!

My colleague Daniel Zabawa and I have written a paper, "How to improve the performance of programs calling mathematical functions -- taking advantage of IBM XL C/C++ or XL Fortran compiler auto-vectorization".

Our paper introduces the IBM MASS high-performance mathematical libraries, and demonstrates how to benefit from them — without the need for source program changes — by using the auto-vectorization capability of the IBM XL C/C++ and XL Fortran compilers. After introducing the concept of auto-vectorization and the associated compiler options, a case study of a discrete Fourier transform program is offered as a real life example of auto-vectorization. Timing results demonstrate that speedups of up to 8.94 times are obtained by the compilers on the example program, via the automatic invocation of MASS by
auto-vectorization.

It is available from IBM developerWorks at the following URL:
http://www.ibm.com/developerworks/rational/library/10/improveperformanceprogramsmathfunctions/index.html

Enjoy!
Robert
#C/C++-compilers-for-AIX
#hpc
#cppcafe
#library
#performance
#vector
#C/C++andFortran