I'm running both GPUGRID and Rosetta on a Linux system. I find that the GPUGRID application seems to be starved for CPU even though it has a lower nice setting than the Rosetta tasks. (I have posted more details at the Ubuntu forum - should I copy that here or can I just point to it? http://ubuntuforums.org/showthread.php?p=10680138#post10680138 )

With Rosetta suspended, GPUGRID is using about 8% of one processor and registers about 90% usage on the GPU (GTX 460) With Rosetta active on all four cores, GPUGRID keeps the GPU at about 10% and uses only about 2% of one core. (This is a 4 core AMD based system.)

Ideally GPUGRID would use sufficient processor to keep the GPU loaded and leave the remainder to Rosetta for maximum performance on both projects. (And yes, I have lots of case fans. ;) )

Are there any Linux or boinc tweaks to achieve this?

thanks,
hank

Hi, I recommend a look at this thread to optimize GPU + CPU.

http://www.gpugrid.net/forum_thread.php?id=2461

Having done the above, to allocate a CPU to a GPU and keep the other in another project (not using GPU) in the BOINC options it is best to book a Core or two more .. GPUs as we have.

Ie if we have 4 Cores will "use a maximum of 75%" of processors or (50% etc ...) as appropriate.

It's like I have it and it works perfectly, I run GPUGRID-(GTX295 +2CPUs) + IBERCIVIS (2CPUs) without conflicts. Greetings

Hi Carlesa25,
Thanks for the tip. I tried the SWAN_SYNC environment variable and it seemed to have no effect.

I really hate to give up 100% of one core for 8% on another project.

I just tried reducing CPU usage from 100% to 95% (in preferences) and that also seems not to help.

thanks,
hank

Hi SWAN_SYNC works and what it does is assign a core to 100% (or almost) to each GPU, GPUGRID performance increases between 10 and 20% according to task, it works better on Linux than Windows (like all Boinc) .

I comment on the use of specific processor is, in "Preferences Using Boinc Manager + Processor + On multiprocessor systems use a maximum of" select that we can use 75% etc ... of processors available on the CPU, ie will be three of the four (or other combination as appropriate)

If we assign A CORE to have four cores and GPUs available, we note use maximum 75% of the CORES thus leave the three remaining free for other tasks without interference with the GPU.

Another thing is the "Maximum Use" of processes, people usually put 60% of time,for general cargo temperatures and PC.
This parameter does not affect the core (or cores) assigned to the variable SWAN_SYNC GPUs, just others.

I do not know if I explained well. Greetings.

Well, where did you put the swan_sync environment variable? Different distros read the environment variable in different places, so YMMV.

EDIT: For instance, I placed the line "export SWAN_SYNC=0" in my /etc/default/boinc-client file (Linux Mint 10). Others have reported that placing it in /etc/environment works, but it didn't work for me.

Hello. In Ubuntu 10.10 should be put in " / etc / environment " in other distributions do not know, if based on Debian in principle be equal ... who whose I guess. Greetings.

Well, where did you put the swan_sync environment variable? Different distros read the environment variable in different places, so YMMV.

EDIT: For instance, I placed the line "export SWAN_SYNC=0" in my /etc/default/boinc-client file (Linux Mint 10). Others have reported that placing it in /etc/environment works, but it didn't work for me.

Hi, What I can say is that in Ubuntu 10.10, / etc / environment, it works perfectly. Greetings.

The effectiveness of adding it to /etc/environment seems to be inconsistent at best. Some distros ignore /etc/environment when starting daemons.

Adding it to the /etc/default file as you did is the best approach. It isolates the scope of the change to the boinc-client (no need to make the variable visible to every process on your system) and it is exactly what the file was intended for.

Hi, What I can say is that in Ubuntu 10.10, / etc / environment, it works perfectly. Greetings.

Actually, I got that advice from you in another thread. Solved the problem I had earlier.

Hi: The problem I see in the solution, is that only works if you have installed Boinc from the classical form.

In a custom configuration, selecting a different place and method of installation /etc/default/-- not have "boinc-client".

For example I have a Boinc installed in a folder /home/carlos/BOINC, this form is the least intrusive on the system, in my opinion and use the form "/etc/environment" is independent of the type of installation.

Personally I am not an expert (amateur only) on Linux (or any other) if I'm wrong I would appreciate your comments. Greetings.

You mean you didn't use a package manager to install BOINC? I'm curious as to why you did that.

Hi, As you know, in Linux, Boinc can be installed in several ways:

View http://boinc.berkeley.edu/wiki/Installing_BOINC

If installed from the Software Center Ubuntu does with the default settings, directories, folders, startup, screensavers etc ...

Through direct download installation package Berkeley, what we have is a file. "sh" an installer that allows Boinc place where we are interested in a directory of your choice or believe in another physical disk etc ... not interfere at all with the OS (without demon etc ...).
We created a program launcher and start or quit when we are interested.

This is not the recommended way to install Boinc, but personally is what interests me and it works perfectly. Greetings.

Hi folks,
I'm now crunching SETI on my GTX 460 and have tried a few things out. I thought I'd share my findings with all of you.

While on GPUGRID, I found that using a real time kernel increased GPU utilization to a range from 35-65% (with 4 instances of Rosetta competing for the CPU.) That only used a couple percent CPU for GPUGRID but the extra overhead for the real time kernel reduced Rosetta throughput about 15% Still that seemed like a decent tradeoff. It was interesting to note that while the GPU utilization seemed to range quite a bit from WU to WU, it was relatively constant for any particular WU.

A Linux/CUDA/Fermi SETI app recently became available so I have switched to that. One characteristic of it is that a single WU seems to cover a wide range of utilization, ranging from 15 to about 85%. (Again, RT kernel and 4 instances of Rosetta.) I found that if I cut back to 3 instances of Rosetta, the SETI WUs ran to completion in about 15 minutes. Next I tried running two instances of SETI and found that WUs now completed in about half an hour. This was no huge surprise, but I was happy that overall throughput was not reduced.

My big surprise was when I added the fourth Rosetta task. GPU utilization remains high at about 85-95% and it appears that throughput will be about the same as if I cut back to three instances of Rosetta. I'm still losing about 15% on Rosetta by using the RT kernel, but at least I'm getting high GPU utilization in return.

I have no way of knowing how this translates to other GPUs, other OSs or other DC projects, but it is certainly something worth further exploration if you're crunching on both CPU and GPU.

happy crunching,
hank

I'm crunching on 3 gpus in my tower and felt that losing a core for a small performance gain seemed kind of pointless. I run a quad core processor and I like to keep it running with tasks from other projects as well as GPUGRID. I tried swan sync and I can say that it works but I feel it's not worth it for 10-15% increase when you can put that core to work doing other helpful things. My gpu's still crank out the work without sacrificing other projects. GPU utilization seems to vary from pc to pc but I find that even with 100% cpu use I'm still getting 60-85% GPU use and that works for me to help keep the temps down. Good luck crunching!
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... GPU utilization seems to vary from pc to pc but I find that even with 100% cpu use I'm still getting 60-85% GPU use and that works for me to help keep the temps down. Good luck crunching!