search for: 24.06

Hi Jack >               dragonegg degg+vectorize degg+optnz  gfortran > ac               12.45       12.45         8.85       8.80 > gas_dyn          11.72       11.80         4.47       4.26 > induct           24.02       24.91        12.08      13.65 > rnflow           32.25       32.35        26.47      24.06 Any idea what might cause such differences here? -- With best

Attached are the Polyhedron 2005 benchmark results for current llvm/dragonegg svn on x86_64-apple-darwin11 built against Xcode 4.3.2 and FSF gcc 4.6.3. The benchmarks for -msse3 and -msse4 appear identical (at least for degg+optnz). This is fortunate since there seems to be a bug in -msse4 on 2.33 GHz (T7600) Intel Core 2 Duo Merom (http://llvm.org/bugs/show_bug.cgi?id=12434).

Hi Anton, >> dragonegg degg+vectorize degg+optnz gfortran >> ac 12.45 12.45 8.85 8.80 >> gas_dyn 11.72 11.80 4.47 4.26 >> induct 24.02 24.91 12.08 13.65 >> rnflow 32.25 32.35 26.47 24.06 > Any idea what might cause such differences

Hi Centos Users The server (ProLiant DL380 G5, Centos 4.3) was not responsible anymore (SSH), fans rotated at full power and the console was blank. After restart it seems to be fine. Now I am analyzing sar statistics (in system logs nothing special, unusual). The hardware monitoring with HP tools didn't work. # sar -P ALL Linux 2.6.9-34.ELsmp (cent061) 01/15/2008 12:00:01 AM

Hi Jack, > Attached are the Polyhedron 2005 benchmark results for current llvm/dragonegg svn > on x86_64-apple-darwin11 built against Xcode 4.3.2 and FSF gcc 4.6.3. thanks for the numbers. How does this compare to LLVM 3.0 - were there any regressions? Ciao, Duncan. The benchmarks > for -msse3 and -msse4 appear identical (at least for degg+optnz). This is fortunate > since

On Tue, Apr 03, 2012 at 09:26:38AM +0200, Duncan Sands wrote: > Hi Jack, > >> Attached are the Polyhedron 2005 benchmark results for current llvm/dragonegg svn >> on x86_64-apple-darwin11 built against Xcode 4.3.2 and FSF gcc 4.6.3. > > thanks for the numbers. How does this compare to LLVM 3.0 - were there any > regressions? The results from just before

Dear group, I have 3 data frames I would like to merge. Here they are: pose16 <- structure(list(DESCRIPTION = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 12L), .Label = c("COPPER May/10", "COTTON NO.2 Jul/10", "CRUDE OIL miNY May/10", "GOLD Jun/10", "ROBUSTA COFFEE (10) Jul/10", "SOYBEANS Jul/10", "SUGAR NO.11

Dear R-helpers, I have two data frames, op and em4: > str(op) 'data.frame': 37 obs. of 5 variables: $ m : num 0.202 0.336 0.122 0.139 0.14 ... $ lln : num 0.798 0.643 0.863 0.835 0.823 ... $ rrn : num 0.789 0.702 0.894 0.895 0.923 ... $ asym2: num 0.177 0.304 0.108 0.187 0.274 ... $ asym3: num 0.0755 0.0975 0.0818 0.0651 0.13 ... > str(rownames(op)) chr

On Tue, 3 Apr 2012 08:57:51 -0400 Jack Howarth <howarth at bromo.med.uc.edu> wrote: > On Tue, Apr 03, 2012 at 09:26:38AM +0200, Duncan Sands wrote: > > Hi Jack, > > > >> Attached are the Polyhedron 2005 benchmark results for current > >> llvm/dragonegg svn on x86_64-apple-darwin11 built against Xcode > >> 4.3.2 and FSF gcc 4.6.3. > > >

Hi all, I've recently run into a situation whereby I need samba to tackle a task. It is complicated by multi-vendor infrastructure. I am hoping that someone here has the knowledge and experience to say: "been there, done that...here is how..." To give some background to the architecture (slightly exotic)... 1. We run a large Sun SAM-FS/QFS installation (a high end

Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation

Attached are the Polyhedron 2005 benchmark results for current llvm/dragonegg svn on x86_64-apple-darwin11 built against Xcode 4.3.2 and FSF gcc 4.6.3. The benchmarks for -msse3 and -msse4 appear identical (at least for degg+optnz). This is fortunate since there seems to be a bug in -msse4 on 2.33 GHz (T7600) Intel Core 2 Duo Merom (http://llvm.org/bugs/show_bug.cgi?id=12434). I've added two

Hello, I plot the abundance of a species in relation to the date. To have the date as a continous variable I put it in the format "standard" in excel (f.ex. 39939 means 06.05.2009). R uses 39939 on the x axis, but I would like to have "06.05". I tried to use as.Date as suggested in some discussion but I don't manage to use it, the returned date is not correct. Do you have

On Tue, Apr 03, 2012 at 08:33:33AM -0500, Hal Finkel wrote: > On Tue, 3 Apr 2012 08:57:51 -0400 > Jack Howarth <howarth at bromo.med.uc.edu> wrote: > > > On Tue, Apr 03, 2012 at 09:26:38AM +0200, Duncan Sands wrote: > > > Hi Jack, > > > > > >> Attached are the Polyhedron 2005 benchmark results for current > > >> llvm/dragonegg svn

So I have a function that does lapply's for me based on dimension. Currently only works for length(pivotColumns)=2 because I haven't fixed the rbinds. I have two versions. One runs WAYYY faster than the other. And I'm not sure why. Fast Version: fedb.ddplyWrapper2Fast <- function(data, pivotColumns, listNameFunctions, ...){ lapplyFunctionRecurse <- function(cdata, level=1,

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