similar to: Conflicts between 'parallel' and 'Rprof', and between two parallel R sessions

hi. i've been very happy using multicore functionality, but felt the need to get more horsepower, so have been trying to use parallel (after realizing it is the "new snow") to access an amazon EC2 cluster, but have had no success. in the internet today, if machine M (the master) can open a connection to machine S (the slave), it's somewhat of a miracle, something to be

Hello All, In general when we use Rprof for performance evaluation on Multicore systems the output provides the time on the basis of the "user" time and the sampling time is equal to the the user time as reported by system.time. This does not seem right behavior when R is linked to BLAS/Lapack or other libraries which are optimized for parallel or multicore architectures as

Hello All, In general when we use Rprof for performance evaluation on Multicore systems the output provides the time on the basis of the "user" time and the sampling time is equal to the the user time as reported by system.time. This does not seem right behavior when R is linked to BLAS/Lapack or other libraries which are optimized for parallel or multicore architectures as

On Mar 30, 2015, at 4:40 PM, Valerie Obenchain <vobencha at fredhutch.org> wrote: > On 03/25/2015 07:48 PM, Simon Urbanek wrote: >> On Mar 25, 2015, at 3:46 PM, Valerie Obenchain <vobencha at fredhutch.org> wrote: >> >>> Hi Simon, >>> >>> I'm having trouble with nested parallel workers, specifically, forking inside socket connections.

Full_Name: Kevin C. Bartz Version: 1.5.1 OS: Solaris 2.6 Submission from: (NULL) (192.223.226.5) A while ago, I noticed this oddity about R profiling and setMethod. First, I "test out" Rprof. > require(methods) Loading required package: methods [1] TRUE > > Rprof("test.out") > data.frame("a") X.a. 1 a > Rprof(NULL) So far, so good. Next, I

Thanks for the report. Will look into it when I get a chance unless someone else gets there first. A simpler reprex: ## create and serialize a memmory-mapped file object filePath <- "x.dat" con <- file(filePath, "wrb") writeBin(rep(0.0,10),con) close(con) library(simplemmap) x <- mmap(filePath, "double") saveRDS(x, file = "x.Rds") ## in a

Hi all, I am not able to export an ALTREP object when `gctorture` is on in the worker. The package simplemmap can be used to reproduce the problem. See the example below ``` ## Create a temporary file filePath <- tempfile() con <- file(filePath, "wrb") writeBin(rep(0.0,10),con) close(con) library(simplemmap) library(parallel) cl <- makeCluster(1) x <- mmap(filePath,

On 03/25/2015 07:48 PM, Simon Urbanek wrote: > On Mar 25, 2015, at 3:46 PM, Valerie Obenchain <vobencha at fredhutch.org> wrote: > >> Hi Simon, >> >> I'm having trouble with nested parallel workers, specifically, forking inside socket connections. >> > > You simply can't by definition - when you fork *all* the workers share the same connection

I noticed this oddity about R profiling and setMethod. First, I "test out" Rprof. > require(methods) Loading required package: methods [1] TRUE > > Rprof("test.out") > data.frame("a") X.a. 1 a > Rprof(NULL) So far, so good. Next, I define myClass. > setClass("myClass", representation(mySlot = "numeric")) [1]

I found that also; fixed in r79386 in the trunk. Will port to R-patched shortly. Best, luke On Thu, 29 Oct 2020, Martin Morgan wrote: > This > > Index: src/main/altrep.c > =================================================================== > --- src/main/altrep.c (revision 79385) > +++ src/main/altrep.c (working copy) > @@ -275,10 +275,11 @@ > SEXP psym =

Full_Name: John Garvin Version: 1.9.0 OS: Linux Submission from: (NULL) (128.42.129.78) This may or may not technically be a bug, but it's certainly an annoyance. Rprof only takes into account computation that occurs inside functions. If a time-consuming operation occurs outside a function, it doesn't record the time it takes. Consider this program 'array.r': Rprof() foo <-

This Index: src/main/altrep.c =================================================================== --- src/main/altrep.c (revision 79385) +++ src/main/altrep.c (working copy) @@ -275,10 +275,11 @@ SEXP psym = ALTREP_SERIALIZED_CLASS_PKGSYM(info); SEXP class = LookupClass(csym, psym); if (class == NULL) { - SEXP pname = ScalarString(PRINTNAME(psym)); + SEXP pname =

Hi, >From reading ?Rprof, I checked R CMD Rprof --help and learned that there are options to specify the min % to print. This is currently (R-devel r52975) displayed with the --help option as --min%total minimum % to print for 'by total' --min%self minimum % to print for 'by self' So I tried R CMD Rprof --min%total 5 and got an error. After looking at

Rprof seems to ignore all time spent inside system() calls. E.g., this simple example actually takes about 10 seconds, but Rprof thinks the total time is only 0.12 seconds: > Rprof("sleep-system.out") ; system.time(system(command="sleep 10")) ; Rprof(NULL) user system elapsed 0.000 0.004 10.015 > summaryRprof("sleep-system.out")$by.total

Yes. It should have something to do with read/write permissions, but it is not clear how it happens. I can write file to C drive using R. I usually write my results matrix to a txt file in C drive. For Rprof(), the boot.out file can be created, but only with one line sample.interval=20000 The situation is the same even if I specify the directory to the D drive,where I have the full

Hello, Appending information to the profiler's output seems to generate problems. Here is a small example of code : <code r> require(boot) Rprof( memory.profiling = TRUE) Rprof(NULL) for(i in 1:2){ Rprof( memory.profiling = TRUE, append = TRUE) example(boot) Rprof(NULL) } </code> The problem is that the file Rprof.out contains more than once the header information: $ grep

I'm having difficulty with Rprof. I have a documentation example test.qss that runs fine without profiling, but under Rprof, > Rprof() > source("test.qss") Error in standardGeneric("model.matrix") : UseMethod used in an inappropriate fashion Luke wrote about a similar circumstance last summer: # From: Luke Tierney (luke@stat.umn.edu) # Date: Fri Jul

Hi, I have searched R mail list archive and couldn't find my answers. The R extension describes how to make use of Rprof to profile R code. gprof can be also used for the same purpose for the C codes when the C codes are written independently and provided with a main() function. I'm currently writing R codes meshed with C Codes, and use .Call as the interface between the two parts.

This looks like a bug? Unable to use scan(pipe()) while profiling. I have no idea whether this version of R violates the "do not use `Rprof' in an executable built for profiling" warning in ?Rprof. Thanks -Don > version _ platform powerpc-apple-darwin1.4 arch powerpc os darwin1.4 system powerpc, darwin1.4 status Patched major 1 minor 3.1 year

I'm trying to use Rprof() to identify bottlenecks and speed up a particullary slow section of code which reads in a portion of a tif file and compares each of the values to values of predictors used for model fitting. I've written up an example that anyone can run. Generally temp would be a section of a tif read into a data.frame and used later for other processing. The first portion