Getting Started with QNX Neutrino - QNX Software Systems

© 2009, QNX Software Systems GmbH & Co. KG. Threads and processes
Threads in mathematical operations
sharing data, such as a web-server that’s serving multiple clients simultaneously. We’ll
examine these two classes.
Suppose that we have a graphics program that performs ray tracing. Each raster line
on the screen is dependent on the main database (which describes the actual picture
being generated). The key here is this: each raster line is independent of the others.
This immediately causes the problem to stand out as a threadable program.
Here’s the single-threaded version:
int
main (int argc, char **argv)
{
int x1;
}
... // perform initializations
for (x1 = 0; x1 < num_x_lines; x1++) {
do_one_line (x1);
}
... // display results
Here we see that the program will iterate x1 over all the raster lines that are to be
calculated.
On an SMP system, this program will use only one of the CPUs. Why? Because we
haven’t told the operating system to do anything in parallel. The operating system isn’t
smart enough to look at the program and say, “Hey, hold on a second! We have 4
CPUs, and it looks like there are independent execution flows here. I’ll run it on all 4
CPUs!”
So, it’s up to the system designer (you) to tell Neutrino which parts can be run in
parallel. The easiest way to do that would be:
int
main (int argc, char **argv)
{
int x1;
... // perform initializations
for (x1 = 0; x1 < num_x_lines; x1++) {
pthread_create (NULL, NULL, do_one_line, (void *) x1);
}
}
... // display results
There are a number of problems with this simplistic approach. First of all (and this is
most minor), the do_one_line() function would have to be modified to take a void *
instead of an int as its argument. This is easily remedied with a typecast.
The second problem is a little bit trickier. Let’s say that the screen resolution that you
were computing the picture for was 1280 by 1024. We’d be creating 1280 threads!
April 30, 2009 Chapter 1 • Processes and Threads 43