My understanding was that threads on Windows is light weight. That is, it should be possible to run multiple threads without excessive memory requirements. In an application that I have just inherited however I am told that each thread takes up the same as the original application. So, the original application takes 10Mb, each additional thread also takes up 10Mb.
This does not tie in with my expectations. So, is it my expectations that are wrong or the code or the setup?
The application is using
Windows 2000 SP4
Active State perl 5.8.6.811
usethreads=define
use5005threads=undef
use ithreads=define
usemultplicity=define
Regards
ICD
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In my case the threads are used simply to carry out a socket connection without wait. The main process makes calls to a module and for each case where a socket connection is to be made a new thread is created to wait for the result of the connection.
All the threads are therefore carrying out the same actien.
Is that the sort of information you were asking for?
Regards
ICD
Not neccessarily. Each thread will create it's own unless you use threads::shared. If you use this module you can share data across threads.
If you are creating variable values inside each thread then these values will be recreated for each local thread and will not be seen or accesible by other threads so in a way it is "recreating the resources for each thread".
Here is an example of each thread performing the same action as the others which creates it;s own variables for each thread.
#!/usr/bin/perl -w
use strict;
use threads;
my ($var1, $var2, $var3) = ("Variable1", "Variable2", "Variable3");
print "\nMain Thread!\n";
print "$var1\n$var2\n$var3\n";
my $count = 0;
for (0..10) {
my $thread = threads->create(\&routine,
$count++;
}
$_->join for (threads->list);
sub routine {
my ($var1, $var2, $var3, $count) = @_;
print "\nThread $count\n";
print "$var1\n$var2\n$var3\n";
}
In this example each child thread would use the same resources as the main thread. However the Main thread will have slighlty more overhead due to creating the threads (the for loop). Once those are created though those resources are released by the main thread.
jmcq
The memory/resources is as reported by windows task manager. If the original application is run (with no threads) then it reports about 10Mb. As the application is run with increasing numbers of threads it increases by about 10Mb per thread.
ZiaTion
I did some tests with your program to measure the memory usage.
With 0 threads the perl process took 3.7Mb
1 thread 4.7Mb
10 threads 8.6Mb
100 threads 48Mb
Is it just me or does this feel excessive? I understand that each thread will require it's own stack so it is not just the amount of (static) data that each thread uses that accounts for the memory increase.
In my own code it is more difficult to isolate the amount of memory used by each thread but the results are similar to those shown in this simple test.
Regards
ICD
I eventually 'worked around' the problem. I devised a method that did not require the need for any extra threads. The application is one where it opens numerous sockets to remote machines. The one thread per socket was just too heavy on memory. The new approach I took today uses just 20kb extra per socket and I have tested it with over 300 simultanious sockets so I am quite happy with the approach.
Thanks ZiaTioN and others for helping me to understand the issues with threads.
Regards
ICD
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by: ZiaTioNPosted on 2005-08-01 at 08:14:33ID: 14570667
Depends on what each thread is performing. If you have an application that is created in the "worker thread model" then this may be a proper indication. Worker threaded model is a threaded model where each thread performs the same function as the others, it is just load balancing. Examples of applications that may use this are things such as a port scanner or a batch processor.
Say you have 1000 payroll files and you want to scan all the files for a specific term. You could create a worker threaded model to pass off 10 files to each of 10 threads and have them scan for your search term and return any matched results. In this case each thread would be performing the same function on the same amount of data (given the files are relatively same size).