Freeradius consuming a lot of memory > 1.6G

["Pshem Kowalczyk" <pshem.k@gmail.com>]

Hi,

We've built a radius-proxy using freeradius and rlm_perl (with
ithreads). Currently we have the following settings:

thread pool {
       start_servers = 20
       max_servers = 100
       min_spare_servers = 20
       max_spare_servers = 50
       max_requests_per_server = 500
}

       perl {
               module = /usr/lib/perl5/rlmPerl.pm

               func_authenticate = authenticate
               func_authorize = authorize
               func_preacct = preacct
               func_accounting = accounting
               func_checksimul = checksimul
               func_pre_proxy = pre_proxy
               func_post_proxy = post_proxy
               func_post_auth = post_auth
               func_xlat = xlat
               func_detach = detach

               max_clones = 100
               start_clones = 20
               min_spare_clones = 20
               max_spare_clones = 100
               cleanup_delay = 5
               max_request_per_clone = 100

       }


The whole setup works fine (there are two machines, load-balanced).
Every single request is piped to the rlm_perl. The number of threads
(ps -eLf) oscillates around 45-50 on both machines. There are no
dealys, or any problems, except for the huge memory consumption.
Authentication request are simply proxied (with minimal changes to the
packets - filtering out some attributes and setting the others, no db
access), accounting is send to a session database (postgresql) on a
separate machine (no load problems there).
Should freeradius use that amount of memory?
The amount of memory is directly linked to the number of threads -
with 25 threads (in the middle of the night) the memory consumption
drops to about 900M.

perl useses the following modules:
use DBI;
use Digest::JHash qw(jhash);
use IPC::Shareable (':lock');
use Storable;

(all variables shared between perl threads are stored in shared memory
using perl IPC).

So the question is should freeradius use that amount of memory and how
can I decrease that?

regards
pshemko