search for: snowed

Problem: I am sorting through model selection process for first time and want to make sure that I have used glm, stepAIC, and update correctly. Something is strange because I get a different result between: 1) a glm of 12 predictor variables followed by a stepAIC where all interactions are considered and then an update to remove one specific interaction. vs. 2) entering all the terms

Hi, Given i have this share : [j.snow] Path = /home/j.snow Share and ntfs permission : j.snow user Now I add another folder share inside the first one : [a.stark] Path = /home/j.snow/a.stark Share and ntfs permission : a.stark user /home/j.snow/a.stark has now parent inherit permission (j.snow) AND a.stark user a.stark can't access to her share ! if I add a.stark NTFS access to [j.snow]

It would be convenient if, under R-devel r56422, packages that require re-installation because they do not have a NAMESPACE were marked as old.packages, so their lack of functionality can be discovered more easily. > "snow" %in% row.names(old.packages()) [1] FALSE > library(snow) Error in library(snow) : package 'snow' does not have a NAMESPACE and should be

Hi there, We're currently attempting to explain a slowdown of an LVQ-type parallel analysis we're working on. We are benchmarking our analysis running over openMosix against the same running via SNOW for R. Both perform similarly on small datasets, but on large datasets SNOW drastically outperforms openMosix. However, these results are achieve running SNOW on the default RedHat

Hi, I am attempting to implement a mixed (windows/linux) snow sockets parallelism in R, but am running into difficulties similar to a post made Aug 31, 2006 under the same subject heading. I feel like I may be one or two non-obvious steps away from getting it all working, but I'm stuck. If anyone can shed some light on this (I believe Prof. Tierney stated that he has successfully run a

Hello, how do you create a histogram with a data frame? year snow.cover 1970 6.5 1971 12.0 1972 14.9 1973 10.0 1974 10.7 1975 7.9 ... mydata=data.frame(year=c(1970,...),snow.cover=c(6.5,...)) hist(mydata) does not work. Many thanks. PR

Hi, I need to understand when is it best to use /rmpi/ and when is it best to use /snow/ for parallel programming in R? I understand snow can be used for a group of non-clustered work stations also. But I wish to understand from the point of view of using both on clusters for a problem which has few chunks of straightforward data-parallelism interleaved with some communication. Since both are

Hello, 1. I have a number of snow depth measurements (centimeters depth) that were acquired in a row (linear transect). A: I am trying to plot the probability density function (PDF) of these points. When I use the "dnorm" command and line type = points, the PDF is displayed correctly. When I change the line type = line, it displays the PDF curve with numerous lines connecting multiple

Full_Name: Roger Peng Version: 1.7.0 OS: Linux (Red Hat 8.0) Submission from: (NULL) (68.64.112.179) There seems to be a problem with R CMD INSTALL using --with-package-versions. First, when using --save and --with-package-versions together, I get the following output (in this case, for the `snow' package): -- marla:> R CMD INSTALL --save --with-package-versions snow_0.1-1.tar.gz *

I have a set of time-series climate data with missing entries. I need to add rows for these missing entries to this data set. The only way I know to do this is unsing a foreloop, but this won't work on a list. I've tried to convert the list to a data frame, but that won't happen, either. I want to fill rows in this table: > newtest[10:15,] yrmos yearmo snow.sum snow.mean

Dear R-users, we are using library(snow) for computation on a linux cluster with RMPI. We have a problem with clusterEvalQ: after launching clusterEvalQ it seems loading the required library on each node but if we type a function belonging to the loaded package R doesn't find it. > library(snow) # making cluster with 3 nodes > cl <- makeCluster(3, type = "MPI") Loading

Guys, I'm running R on both Windows & Linux. I'm looking at a number of packages for parallel execution. It seems that the most used packages are "snow" and "Rmpi". snow seems more user friendly, but it doesn't run on windows. I see from searching the mailing list that I'm not the first one to try it on Windows. There was a message that kind of shed some

We got some errors and eventually figured out that parallel::clusterExport second argument is "varlist" while in snow::clusterExport it is "list". The user had loaded parallel first, but did something else which inadvertently loaded snow, then clusterExport failed because we had "varlist" and not "list". Are these different on purpose? pj -- Paul E.

I am slightly confused by the way the standard output is redirected in a R snow cluster environment. I am using parLapply from the snow package to execute a function on my MPI/LAM cluster. How can I redirect standard output (produced using "cat") from this function back to the terminal where I invoked it? I intend to transmit some status information in advance to the final result of the

Dear All, I am learning parallel in R and start with the package "snow". I did a test about running time and the parallel version is much slower than the regulat code. My laptop is X200s with dual core intel L9400 cpu. Should I make more clusters than 2? Or how to improve the performance? # install.packages("snow") library(snow) cl <- makeCluster(2) t1 <- proc.time() a

Hi, I have few high-level questions about the Snow and Rmpi packages . I understand that Snow uses Rmpi as one of possible transport layers, yet my questions about user experience, not technical details: 1. Does Snow install and work well in Windows? 2. Interruptibility. I understand that currently it is impossible to interrupt a running top-level command in Snow ( Ctl-c or the likes), the

Dear Luke and others, I have many R versions on my machine and want to start a particular one when snow builds its cluster. (The same version I start snow from.) It seems that everything is set up correctly in defaultClusterOptions: > mget(ls(defaultClusterOptions), defaultClusterOptions) $homogeneous [1] TRUE $manual [1] FALSE $master nodename "maya.unil.ch" $outfile [1]

Dear everyone, I am trying to run rgenoud on several chips simultaneusly. I used the instructions provided on Jasjeet Sekhon's Homepage (http://sekhon.berkeley.edu/rgenoud/multiple_cpus.html). However, I have the newer version of R (R 2.12) installed - for a 64-bit machine. So, when I tried to install the special version of "snow" from a zip file provided by Jasjeet on his page, R

Hello All, I can run the "lower level" functions OK, but many of the higher level (eg. parSApply) functions are generating errors. When running the example (from the snow help docs) for parApply on MacOSX 10.5.5, I get the following error: cl <- makeSOCKcluster(c("localhost","localhost")) sum(parApply(cl, matrix(1:100,10), 1, sum)) Error in

The command which hangs: I'm hoping there is a simple explanation, but I searched on-line and nothing jumped out. > cl <- makeCluster(type="SOCK",c("localhost"),manual=TRUE) Manually start worker on localhost with C:/PROGRA~1/R/R-214~1.2/bin/Rscript.exe "C:/Program Files/R/R-2.14.2/library/snow/RSOCKnode.R" MASTER=localhost PORT=11944 OUT=/dev/null