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Hi! I'm having some problem with our setup. I have a linux server authenticating from a win2k3 domain controller via winbind and pam. When i try to log in I receive the following error messages: Jul 3 10:26:10 zeusz pam_winbind[20375]: user 'tamas' granted access Jul 3 10:26:10 zeusz pam_winbind[20375]: user 'tamas' OK Jul 3 10:26:10 zeusz pam_winbind[20375]: user

On Sat, Jun 01, 2013 at 06:45:48AM +0200, Duncan Sands wrote: > > These results are very disappointing, I was hoping to see a big improvement > somewhere instead of no real improvement anywhere (except for gas_dyn) or a > regression (eg: mdbx). I think LLVM now has a reasonable array of fast-math > optimizations. I will try to find time to poke at gas_dyn and induct: since >

Hi all, Sorry for the offtopic question. I hope though that others on this list or reading the archive find the answers useful too. It seems the Adaptec 1405 4port SAS HBA I bought only works with RHEL and SuSE through a closed source driver, and thus is quite useless :-( I was stupid enought to think "Works with RHEL and SuSE" meant "Certified for RHEL and SuSE, but driver in

Hi Jack, thanks for splitting out what the effects of LLVM's / GCC's vectorizers is. On 01/06/13 21:34, Jack Howarth wrote: > On Sat, Jun 01, 2013 at 06:45:48AM +0200, Duncan Sands wrote: >> >> These results are very disappointing, I was hoping to see a big improvement >> somewhere instead of no real improvement anywhere (except for gas_dyn) or a >> regression

Hi Jack, On 29/05/13 22:04, Jack Howarth wrote: > On Wed, May 29, 2013 at 03:25:30PM +0200, Duncan Sands wrote: >> Hi Jack, I pulled the loop vectorizer and fast math changes into the 3.3 branch, >> so hopefully they will be part of 3.3 rc3 (and 3.3 final!). It would be great >> if you could redo the benchmarks rc3. >> > > Duncan, > As requested, appended

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

On Sat, 2011-10-29 at 15:16 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > > Ralf, et al., > > > > > > Attached is the latest version of my autovectorization patch. llvmdev > > > has been CC'd (as had been suggested to me); this e-mail contains > >

Hello, Using the following lines of code, I created the following graph:

Hello, Using the following lines of code, I created the following graph:

Jack, Can you please file a bug report and attach the BC files for the major loops that we miss ? Thanks, Nadav On Jun 2, 2013, at 1:27, Duncan Sands <duncan.sands at gmail.com> wrote: > Hi Jack, thanks for splitting out what the effects of LLVM's / GCC's vectorizers > is. > > On 01/06/13 21:34, Jack Howarth wrote: >> On Sat, Jun 01, 2013 at 06:45:48AM +0200,

On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > Ralf, et al., > > > > Attached is the latest version of my autovectorization patch. llvmdev > > has been CC'd (as had been suggested to me); this e-mail contains > > additional benchmark results. > > > > First, these are preliminary

Hi Hemant, As I suspected, the code broke when I got to the line: result <- rfm_auto(df, id="user_id", payment ="subtotal_amount", date="created_at") Error in rfm_auto(df, id = "user_id", payment = "subtotal_amount", date = "cr eated_at") : could not find function "rfm_auto" It looks like you are using the hoxo-m/easyRFM

I'm trying to perform an RFM analysis on the attached dataset, I'm able to get the results using the auto_rfm function but i want to define my own breaks for RFM. as follow r <-c(30,60,90) f <-c(2,5,8) m <-c(10,20,30) but when i tried to define my own breaks i got the identical result for RFM i.e 111 for every ID. please help me with this with working R script so that i can get

Actually this kind of opportunities, as outlined bellow, was one of my contrived motivating example for fast-math. But last year we don't see such opportunities in real applications we care about. t1 = x1/y ... t2 = x2/y. I think it is better to be taken care by GVN/PRE -- blindly convert x/y => x *1/y is not necessarily beneficial. Or maybe we can blindly perform such

Dear list, First my information: platform i386-pc-linux-gnu arch i386 os linux-gnu system i386, linux-gnu status major 2 minor 3.1 year 2006 month 06 day 01 svn rev 38247 language R version.string Version 2.3.1 (2006-06-01) Now my question: How is it possible that a command in an R script is not

On Feb 19, 2011, at 11:25 AM, Jack Howarth wrote: > Is anyone able to bootstrap llvm-gcc42 svn on x86_64-apple-darwin10? Currently it is > failing here with... It was broken. I think I've fixed it in reverting 125960. -eric

On Mon, Feb 21, 2011 at 03:58:19PM -0800, Eric Christopher wrote: > > On Feb 19, 2011, at 11:25 AM, Jack Howarth wrote: > > > Is anyone able to bootstrap llvm-gcc42 svn on x86_64-apple-darwin10? Currently it is > > failing here with... > > It was broken. I think I've fixed it in reverting 125960. > > -eric Eric, The llvm-gcc42 bootstrap is fixed in

On Thu, May 23, 2013 at 03:40:00PM +0200, Duncan Sands wrote: > Hi Jack, > > On 23/05/13 15:37, Jack Howarth wrote: >> Below are the results for the Polyhedron 2005 benchmarks compiled with llvm/compiler-rt/dragonegg 3.3svn at r182439 against current >> FSF gcc 4.7.3svn and 4.8.1svn. The only major bug remaining in the dragonegg 3.3svn support for gcc 4.8.x is

If x has an S3 class then sort.int(x) returns a value without an S3 class but which has the is.object flag set, which, I think, causes identical() give a false/misleading report: > x <- structure(1:3, class="unrecognizedClass") > y <- sort.int(x) > t <- 1:3 > identical(y, t) # expect TRUE [1] FALSE > identical(as.vector(y), as.vector(t)) # expect

On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > Ralf, et al., > > Attached is the latest version of my autovectorization patch. llvmdev > has been CC'd (as had been suggested to me); this e-mail contains > additional benchmark results. > > First, these are preliminary results because I did not do the things > necessary to make them real (explicitly quiet the