search for: preschedules

I've been using mclapply and have encountered situations where it gives errors or returns incorrect results. Here's a minimal example, which gives the error on R 2.15.2 on Mac and Linux: library(parallel) f <- function(x) NULL mclapply(1, f, mc.preschedule = FALSE, mc.cores = 1) # Error in sum(sapply(res, inherits, "try-error")) : # invalid 'type' (list) of argument

Hello, Consider this: 1) library(parallel) res <- mclapply(1:2, stop) #Warning message: #In mclapply(1:2, stop) : # all scheduled cores encountered errors in user code is(res[[1]], 'try-error') #[1] FALSE 2) library(parallel) res <- mclapply(1:2, stop, mc.preschedule=FALSE) #Warning message: #In mclapply(1:2, stop, mc.preschedule = FALSE) : # 2 function calls resulted in an

Hi, there seem to be some (small) bugs in the mclapply function in parallel. I discovered this in the current R release version, and I checked that it is still present in R-devel. I think it only occurs in the part of the code corresponding to argument option mc.preschedule = FALSE. Here are two examples: a) library(parallel) mclapply(list(), identity, mc.preschedule=FALSE) Error in

Dear members, I am using pbmcapply to parellise my code. But the following code doesn't work: > LYG <- pbmclapply(LYGH,FUN = arfima,mc.cores = 2,mc.preschedule = FALSE) | | 0%, ETA NA^ It just hangs. But the

Quick question regarding multicore versions of mapply. Package 'multicore' provides a parallelized version of 'lapply', called 'mclapply'. I haven't found any parallelized versions of 'mapply', however (although one can use the lower level function 'parallel', it becomes harder to control the number of spawned processes etc). Is anyone aware of a

On Fri, 9 Jun 2023 18:01:44 +0000 akshay kulkarni <akshay_e4 at hotmail.com> wrote: > > LYG <- pbmclapply(LYGH,FUN = arfima,mc.cores = 2,mc.preschedule = > > FALSE) > | > | > 0%, ETA NA^ > > It just hangs. My questions from the last time still stand: 0) What is your

Hi, At the moment the same test is being ran twice - same output so pointless! I believe this may not be what was intended. The change below runs the virtual register test the second time on the Predecessor SUnit. Robert diff --git a/lib/CodeGen/SelectionDAG/ScheduleDAGRRList.cpp b/lib/CodeGen/SelectionDAG/ScheduleDAGRRList.cpp index f5fe168..6e888da ---

Hi all, I'm trying to use the package read.table within a foreach loop. I'm grabbing 500M rows of data at a time from two different files and then doing an aggregate/tapply like function in read.table after that. I had planned on doing a foreach loop 39 times at once for the 39 files I have, but obviously that won't work until I figure out why the segfault is occurring. The

Here is a bit more data. After PrescheduleNodesWithMultipleUses has been run, the following Predecessor/Successor links are 'dumpAll'ed. (I attach the full dumpAll before & after "Prescheduling SU #7 next to PredSU #4 to guide scheduling in the presence of multiple uses") SU(3) Predecessors: val SU(5): Latency=1 ch SU(7): Latency=1 val SU(7): Latency=1 SU(7):

I try to move from SPSS to R/S and am trying to reproduce the results of SPSS in R. I calculated a one-way anova with "spk" as experimental factor and erp as depended variable. The result of the Anova are the same concearning the mean square, F and p values. But I also wanted to caculate the contr.sdif(4) contrast on spk. The results are completely different now. I hope anybody can

Hi, I have an assert firing due to PickNodeToScheduleBottomUp(): 1. having a CallResource in use pushing an interference of current SUnit. 2. having no more SUnits in the AvailableQueue 3. The only interference being the SUnit that just failed due to a Call Resource. 4. An attempt to duplicate this node which has the 'Call Resource' as a physical register. Thus the call

Hi, I have reasoned through and believe the problem is with the PrescheduleNodesWithMultipleUses. Take the following DAG (arrow to predecessor): Destroy Destroy ^ ^ | | | | SetUp----->PredSU <-----SU ^ ^ ^ | | | | | | ----------- |

Hey folks, Is there any way to exit an mclapply early on error? For example, in the following mclapply loop, I have to wait for all the processes to finish before the error is returned. ``` mclapply(X = 1:12, FUN = function(x) {Sys.sleep(0.1); if(x == 4) stop()}, mc.cores = 4, mc.preschedule = F) ``` When there are many calculations in FUN, it takes a long time before the error is returned.

The build system rolled up R-4.0.1.tar.gz (codename "See Things Now") this morning. The list below details the changes in this release. You can get the source code from http://cran.r-project.org/src/base/R-4/R-4.0.1.tar.gz or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course. For the R Core Team, Peter Dalgaard

The build system rolled up R-4.0.1.tar.gz (codename "See Things Now") this morning. The list below details the changes in this release. You can get the source code from http://cran.r-project.org/src/base/R-4/R-4.0.1.tar.gz or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course. For the R Core Team, Peter Dalgaard

The build system rolled up R-4.0.1.tar.gz (codename "See Things Now") this morning. The list below details the changes in this release. You can get the source code from http://cran.r-project.org/src/base/R-4/R-4.0.1.tar.gz or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course. For the R Core Team, Peter Dalgaard

Dear R-Users, I run a MC-Simulation using the the packages "foreach" and "doMC" on a PowerMac with 24 cores. There are roughly a hundred parametersets and I parallelized the program in a way, that each core computes one of these parametersets completely. The problem ist, that some parametersets take a lot longer to compute than others. After a while there are only a quarter

Hi Andreas, the error is reported when some child process cannot send results to the master process, which originates from an error returned by write() - when write() returns -1 or 0. The logic around the writing has not changed since R 3.5.2. It should not be related to the printing in the child, only to returning the value. The problem may be originating from the execution environment,

...o give a thourough update of the MI scheduler. Hopefully that will answer many of your questions. Some important things changed between the time I introduced the MI scheduler a year ago, and the release of 3.3. The biggest change was loop vectorization, which reduces register pressure and somewhat preschedules loops. Since 3.3 was released, the generic MI scheduler's heuristics were reevaluated in preparation for making it the default for targets without a custom scheduling strategy--more on that later. The source order scheduler was also fixed so that it actually preserves IR order, which is at leas...

Hi, I am facing a very weird problem with parallel::mclapply. I have a script which does some data wrangling on an input dataset in parallel and then writes the results to disk. I have been using this script daily for more than one year always on an EC2 instance launched from the same AMI (no updates installed after launch) and processed thousands of different input data sets successfully. I now