On Fri, Jan 18, 2013 at 12:53 AM, Ole Tange
<tange@gnu.org> wrote:
On Thu, Jan 17, 2013 at 12:58 PM, Nanditha Rao <
nanditha.ec@gmail.com> wrote:
> 1. I need to run multiple jobs on a multicore (and multithreaded) machine. I
> am using the GNU Parallel utility to distribute jobs across the cores to
> speed up the task. The commands to be executed are available in a file
> called 'commands'. I use the following command to run the GNU Parallel.
>
> cat commands | parallel -j +0
>
> As per the guidance at this location- gnu parallel, this command is supposed
> to use all the cores to run this task. My machine has 2 cores and 2 threads
> per core.
[Nanditha: I guess so. I am using an Intel core i3 laptop to test this tool out..]
> The system monitor however shows 4 CPUs (CPU1 and CPU2 belong to
> core1, CPU3 and CPU4 belong to core2). Each job (simulation) takes about 20
> seconds to run on a single core. I ran 2 jobs in parallel using this GNU
> parallel utility with the command above. I observe in the system monitor
What system monitor are you using?
[Nanditha: gnome-system-monitor on ubuntu]
> that, if the 2 jobs are assigned to cpu1 and cpu2 (that is the same core),
> there is obviously no speed-up.
Why obviously? Normally I measure a speedup of 30-70% when using hyperthreading.
[Nanditha: I somehow dont see a speedup. Running a single job on single thread on single core versus two threads on the same core is taking the same time- about 20seconds]
> They take about 40seconds to finish, which
> is about the time they would take if run sequentially. However, sometimes
> the tool distributes the 2 jobs to CPU1 and CPU3 or CPU4 (which means, 2
> jobs are assigned to 2 different cores). In this case, both jobs finish
> parallely in 20 seconds.
GNU Parallel does not do the distributing; it simply spawns jobs. The
distribution is done by your operating system.
> Now, I want to know if there is a way in which I can force the tool to run
> on different "cores" and not on different "threads" on the same core, so
> that there is appreciable speed-up. Any help is appreciated. Thanks!
If you are using GNU/Linux you can use taskset which can set a mask on
which cores a task can be scheduled on. If you want every other:
1010(bin) = 0xA. For a 128 core machine you could run:
cat commands | taskset 0xaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa parallel -j +0
[Nanditha: Tried this, thanks. But seems like it doesnt help speedup the jobs as assumed by me earlier]
> 2. Also, I want to know if there is a way to run this utility over a cluster
> of machines.. say, there are four 12-core machines in a cluster (making it a
> 48-core cluster).
cat commands | parallel -j +0 -S server1,server2,server3,server4
[Nanditha: I tried this option. cat commands|parallel -j +0 --sshlogin username@ip_address
However, I get an error that the files listed the 'commands' file are not to be found. Basically I am running a simulation and invoking the commands through the file called 'commands'. Is there some path I need to specify as to where they should get copied in the destination server? Or by default where does it get copied to and where do I go to see my results file. This is the error I get (where each file is part of the command that I specify in 'commands':)
decoder_node_1_line0_sim_4.sp: No such file or directory
decoder_node_1_line0_sim_3.sp: No such file or directory
decoder_node_1_line0_sim_1.sp: No such file or directory
decoder_node_1_line0_sim_2.sp: No such file or directory
My commands file contains:
ngspice decoder_node_1_line0_sim_1.sp
ngspice decoder_node_1_line0_sim_2.sp
ngspice decoder_node_1_line0_sim_3.sp
ngspice decoder_node_1_line0_sim_4.sp
and the tool parallel is being invoked from the directory in which these files are present. So, I expect that the tool should pick these files up from the current directory and distribute it to the server and run them. It runs locally on my machine, but the -S option gives me the above error. Can you pls suggest?
Thanks!
Please read http://www.gnu.org/software/parallel/man.html#example__using_remote_computers
or watch the intro videos:
https://www.youtube.com/playlist?list=PL284C9FF2488BC6D1
/Ole