improving numerical applications performance
improving numerical applications performance
- Subject: improving numerical applications performance
- From: Amilcar Meneses Viveros <email@hidden>
- Date: Mon, 17 May 2004 12:54:10 -0500 (CDT)
Hello. I had read some articles about Altivec, my main question is
how can I improve the performance for numerical applications? (of
course I know about complexity and things like that) but, for example, I
had the oportunity to see the performance for a numeric program (a triple
integral) and the times in my powerPC (400MHZ with 512 Ram) was slower
that another machines (Intel 2.66GHZ, 3GHZ and 1.5GZH with Linux).
The following table has a better information:
OS Mac OS X | Linux | Solaris | Linux
CPU POWER PC | Pentium4 | SPARC | Pentium4 Xeon
SPEED 400 MHZ | 1.5 GHZ | 2GHZ | 3.06GHZ
RAM 512MB | 256MB | 512MB RAM | 512MB
-------------------+-----------+-----------+------------
TIME 372.95min | 134.58min | 264.6min | 65.5min
Of course its possible that the source code could be improve for better
performance, but we ran the same code in severals plataforms.
The program was compiled with -O3 optimization in alls plataforms (in
Solaris case I used the -xO3 optimization),and the execution time was
obtained by the command "time".
I know that the speed of anothers CPU is faster than my powerPC, but if I
have an Altivec, how can I improve the performance of a numeric
application in a simple way? (i.e. from the gcc compiler)
I have notice tha compilers like vcc can improve the performance if
you work with float data, but not with a double data. But, many
mathematics functions of the library are (by defautl) in double, and what
can I do whether I really need a double precision?
Perhaps I used a bad tool for measure the time, in such case, somebody
know a better way for do it?
Regads
Amilcar
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