An example of poor C++ performance

[Steve C. Thompson]

Hello Group,

My previous posts have been leading up to this.  I have successfully
converted my m-file simulation code to C++, which can then be loaded as
an .oct module.  To test speed improvements, I've made a simple example
comparing the simulation with two approaches:

1) pure m-file (vectorized)
2) m-file/C++ hybrid

Each approach generates about 1e9 random numbers.  The pure m-file is
vectorized by crunching numbers in 1e4 blocks (which I've found to be
optimum on my machine).  However, over 50,000 loops are required.  The
hybrid m-file/C++ diverts the looping C++.  This approach only has 46
m-file loops and the rest is done in the compiled module.  For each C++
loop a couple random number are generated with the command
octave_rand::scalar().

I was expecting C++ implementation to outperform the pure m-file
approach, but this isn't the case.

My feeling is that the octave_rand::scalar() is a bottleneck.  Would it
be faster to call MT
(http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html) directly and
sidestep Octave's oct-rand.h header? In ``Octave: Past, Present, and
Future'' (2001) JWE says that there is overhead with octave_value.  Is
the convenience of using the Octave headers and making the .oct module
resulting in a slower C++ implementation?

Please advise.

The source files with more discussion can be found at
http://elsteve.com/test_oct/index.html#bpsk_ber

Thanks,
Steve



-------------------------------------------------------------
Octave is freely available under the terms of the GNU GPL.

Octave's home on the web:  http://www.octave.org
How to fund new projects:  http://www.octave.org/funding.html
Subscription information:  http://www.octave.org/archive.html
-------------------------------------------------------------