On Sat, 26 Apr 2008, Jiří Voller wrote:
Dear R-users,
I run my program a difference between sys.times is as follows:
user system elapsed
60167.53 2848.75 63278.93
I am quite puzzled how it may happen that system time is so much shorter
than user time, I have 2 core computer most of the time (90%) I was not
doing anything else with the computer. What could be the reason of such a
difference? I switched off file indexing and all other resident
programs...... My program include writing output into a file - could that be
the reason?
First, do you mean system.time()? Its help page refers you to ?proc.time,
which says:
An object of class '"proc_time"' which is a numeric vector of
length 5, containing the user, system, and total elapsed times for
the currently running R process, and the cumulative sum of user
and system times of any child processes spawned by it on which it
has waited. (The 'print' method combines the child times with
those of the main process.)
and it seems you don't know those terms. At any given time a CPU is
running a task for a process, it is either in a system call or in user
code (R itself or a package). This is recorded every once in a while (a
few ms) and totalled. So your process spent 2848s in system calls.
The elapsed time is a little more than the sum of the user and system
times, as your R session was not running 100% of the time.
You didn't even tell us your OS (see the posting guide) nor your
background . On a Unix-alike look at the man pages for time and times.
E.g. mine says
The tms_utime field contains the CPU time spent executing instructions
of the calling process. The tms_stime field contains the CPU time
spent in the system while executing tasks on behalf of the calling process.
Thanks for your replies.
--
--------------------------------------------------------------------------------------------
Ji?? Voller
Laboratory of Growth Regulators
Palack? University & Institute of Experimental Botany AS CR
?lechtitel? 11, 783 71 Olomouc
Czech Republic
http://rustreg.upol.cz
landline: +420-585-634-855
cell: +420-737-520-506
fax: +420-585-634-870
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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