search for: spents

Hello R help! I am extremely new to R (as in 3 just days) and I've been using it to do some pretty basic things. I am frustratingly stuck on one point, and am so so so close to figuring it out, but just far enough away to ask for some (perhaps embarrassingly easy) help. I have a dataset, visitors, that has a variable called Time.Spent. Time.Spent consists of times in the format hh:mm:ss ,

Hello, I'm working on an Asterisk configuration for a call center, and they bill based on the time spent talking to an agent, but not for any time spent waiting in a queue. The CDR information contains the entire duration of the call as billable seconds, including time spent waiting in the queue. I would like the billable seconds to only include the time spent actually talking to an agent.

Hi, having running centOS-4.4 on a really fast machine (16 GB memory, 8 Opteron CPU's, SATA drives). Then making an update by using the Centos-5 CD's. The start was fast, but during update, the installer spents a very, very long wallclock time during selinx updating: for about 1/2 hour the updater runs in a restorecon/find sequence. And at the end, before the MBR is written, it spents again a long time in "install". Can somebody explain this? Regards -- Joachim Backes <joachim.backes at...

Thanks Kristof. Sounds like we'll need to investigate though I'd say it is not blocking the switch. At this point I think everybody is on board to flip the switch. @Eric, how does that sound to you? Thanks, Q > Le 1 juin 2017 à 07:46, Kristof Beyls <Kristof.Beyls at arm.com> a écrit : > > >> On 31 May 2017, at 17:07, Quentin Colombet <qcolombet at

Hi all, I added a buildbot [1] running the test-suite with -O0 -global-isel. It runs into the same 2 timeouts that I reported previously on this thread (paq8p and scimark2). It would be nice to make it green before flipping the switch. At the moment, it lives in an internal buildmaster that I've setup for this purpose. If we fix it and it proves to be stable for a week or two, I'll move

Hi there, (context: I was optimizing Roundcube mailbox list server response, and in that 300-400ms response time, around 170ms is spent on single fgets() call which is waiting IMAP repsonse to "SELECT MyMailbox" command) I straced dovecot and of the whole request/response process, around 30ms is spent for everything else, and overwhelming majority of time (150-170ms) is spent for

On Mon, Mar 16, 2015 at 1:54 AM, Davide Italiano <davide at freebsd.org> wrote: > > Shankar's parallel for per-se didn't introduce any performance benefit > (or regression). > If the change I propose is safe, I would like to see Shankar's change > in (and this on top of it). > I have other related changes coming next, but I would like to tackle > them one at

Dear R-users, I have an outcome variable and I'm unsure about how to treat it. Any advice? I have spending data for each county in the state of California (N=58). Each county has been allocated money to spend on any one of the following four categories: A, B, C, and D. Each county may spend the money in any way they see fit. This also means that the county need not spend all the money that

Hi list, I have data in a dataframe t1, with a column for different amounts spent, a column what it was spent on, and a column with dates, from which I create a new column with months. Example: amount <- rep(c(10,20,30),3) what <- rep(c("food","books","cycling"),3) when <- c(rep("2008-09-05",5),rep("2008-10-07",4)) t1 <-

Hi Kristof, Thanks for the updated numbers. > On May 31, 2017, at 7:45 AM, Kristof Beyls <kristof.beyls at arm.com> wrote: > >> >> On 31 May 2017, at 15:33, Diana Picus via llvm-dev <llvm-dev at lists.llvm.org <mailto:llvm-dev at lists.llvm.org>> wrote: >> >> Cool test :) >> It seems to work fine now, I don't see any new failures.

I have several data frames, each with six variables and several hundred cases broken out from a larger dataframe by eleven values of a factor called "Division". I have to perform the same analysis on each one. I would like to do it by creating a data frame called data2 eleven times, once with data corresponding to each value of the factor, and performing the same analysis on each of

Hey guys, I'm working on the S3D Benchmark and notice that CodeGenPrepare::OptimizeMemoryInst(...) in lib/Transforms/Scalar/CodeGenPrepare.cpp isn't scaling well. A whopping 99.3% of the compilation time for one file is spent in this function. The User Time for this compilation is 3166 seconds with a stock LLVM 3.1. If I disable the calls to OptimizeMemoryInst(...), the compilation time

So I finally took the plunge and switched to MCJIT (wasn't too bad, as long as you remember to call InitializeNativeTargetDisassembler if you want disassembly...), and I got the functionality to a point I was happy with so I wanted to test perf of the system. I created a simple benchmark and I'd thought I'd share the results, both because I know I personally had no idea what the

I’m taking a first look at InstCombine performance. I picked up the caching patch and ran a few experiments on one of our larger C++ apps. The size of the *.0.2.internalize.bc no-debug IR is ~ 30M. Here are my observations so far. Interestingly, caching produced a slight but measurable performance degradation of -O3 compile time. InstCombine takes about 35% of total execution time, of which ~20%

hi, I am trying to find out the avg cpu time spent in each of my user methods (exclusive of other methods invoked by a method). Hence the following snippet failed miserably: ----------------------- pid$target:a.out::entry { time[probefunc] = timestamp;} pid$target:a.out::return { @spent[probefunc] = avg(timestamp - time[probefunc]);} END { printa(@spent);}

Rafael, Your latest benchmark results look great. LLD took 1.38 seconds where gold --threads takes 0.85 seconds. It needs to be faster, but that's not too bad. On Thu, Mar 19, 2015 at 10:13 AM, Rafael Espíndola < rafael.espindola at gmail.com> wrote: > > Here's an update. > > > > After http://reviews.llvm.org/D8372 , I updated the profiling data. > > >

On Tue, Jul 16, 2013 at 1:18 PM, Xinliang David Li <xinliangli at gmail.com>wrote: > Ignoring FE time which can be fully parallelized and assuming 10% > compile time is spent in serial module passes, 25% time is spent in > CGSCC pass, the maximum speed up that can be gained by using function > level parallelism is less than 3x. Even adding support for parallel > compilation

Okay, so I spent a lot of time locating the patch that prevents me from moving my application, GSAK, from 0.9.16 to the latest version of wine. I spent a lot of time recompiling different bisected versions of wine in order to do just that. I even submitted a bugzilla report. As it turns out, it was the patch I suspected when I first started. It seems that the dependency on the Mozilla Active X

On 12 June 2017 at 18:54, Diana Picus <diana.picus at linaro.org> wrote: > Hi all, > > I added a buildbot [1] running the test-suite with -O0 -global-isel. It > runs into the same 2 timeouts that I reported previously on this thread > (paq8p and scimark2). It would be nice to make it green before flipping the > switch. > > I did some more investigations on a machine

On Tue, Apr 10, 2018 at 1:44 PM Richard W.M. Jones <rjones@redhat.com> wrote: > We now have true zeroing support in oVirt imageio, thanks for that. > > However a problem is that ‘qemu-img convert’ issues zero requests for > the whole disk before starting the transfer. It does this using 32 MB > requests which take approx. 1 second each to execute on the oVirt side. >