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Hi Team Can someone advice me on how i can lower the load average on my asterisk server? dahdi-linux-2.1.0.4 dahdi-tools-2.1.0.2 libpri-1.4.10.1 asterisk-1.4.25.1 2 X TE412P Digium cards on ISDN PRI Im using the system as an IVR without any transcoding or bridging ************************************** top - 10:27:57 up 199 days, 5:18, 2 users, load average: 67.75, 62.55, 55.75 Tasks: 149

I have an old A1 ISDN card that we used to use in the mid 1990's for the delivery of data to our ISP I have seen some users have been using them, with respect to doing web searches. Can someone please let me know what drivers I require to use this card under debian and with asterix, and what the limitations are of using this card. I dont want to make calls but do inbound using it. The

Hi all, Ok, I'm making progress on my new server, but there is an entry in the logs on the old/current server that is not showing p on the new one... lines like: dovecot: auth-worker(20284): mysql(localhost): Connected to database my_auth_db I've looked everywhere, compared settings, etc, and can't seem to find why I get this line on the old server and odn't on the new one.

Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation

Not everytime but most times when I close a program I get the application box and in the backtrace box the error is always the same. I've attached the blacktrace log. Besides this KDE functions fine and never happens when using an application on when closing one. Bri, -------------- next part -------------- (no debugging symbols found)...(no debugging symbols found)... (no debugging

During a stress test dovecot-2.0.11 logs many warnings: Mar 8 06:19:52 gromit dovecot[59204]: imap(pid 68864 user user15): Warning: /Volumes/Mail/user15/dovecot-uidlist: Duplicate file entry at line 183: 1299556557.M571530P31883.gromit.example.com,S=21175,W=21549 (uid 67 -> 250) Mar 8 06:20:10 gromit dovecot[59204]: imap(pid 68865 user user34): Warning: /Volumes/Mail/user34/dovecot-uidlist:

The code bekow works so this is why I didn't include the data to reproduce it. The loops about 500 times and each time, a zoo object with 1400 rows and 4 columns gets created. ( the rows represent minutes so each file is one day worth of data). Inside the loop, I keep rbinding the newly created zoo object to the current zoo object so that it gets bigger and bigger over time. Eventually,

Instrumentation based Profile Guided Optimization (PGO) is a compiler technique that leverages important program runtime information, such as precise edge counts and frequent value information, to make frequently executed code run faster. It's proven to be one of the most effective ways to improve program performance. An important design point of PGO is to decide where to place the

Accidentally sent to uiuc server. On Fri, Aug 7, 2015 at 10:49 PM, Sean Silva <chisophugis at gmail.com> wrote: > Can you compare your results with another approach: simply do not > instrument the top 1% hottest functions (by function entry count)? If this > simple approach provides most of the benefits (my measurements on one > codebase I tested show that it would eliminate

On Sat, Aug 8, 2015 at 6:31 AM, Xinliang David Li <davidxl at google.com> wrote: > On Fri, Aug 7, 2015 at 10:56 PM, Sean Silva <chisophugis at gmail.com> wrote: > > Accidentally sent to uiuc server. > > > > > > On Fri, Aug 7, 2015 at 10:49 PM, Sean Silva <chisophugis at gmail.com> > wrote: > >> > >> Can you compare your results

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934