Displaying 5 results from an estimated 5 matches for "mclappy".
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mclapply
2011 Oct 09
1
convert apply to lappy
Dear all I want to convert a apply to lapply. The reason for that is that there is a function mclappy that uses exact the same format as the lapply function.
My code looks like that
mean_power_per_tip <- function(data) {
return((apply(data[,],2,MeanTip)));
}
where data is a [m,n] matrix.
I would like to thank you in advance for your help
B.R
Alex
[[alternative HTML version deleted...
2012 Dec 31
3
weird bug with parallel, RSQlite and tcltk
Hello,
I spent a lot of a time on a weird bug, and I just managed to narrow it down.
In parallel code (here with parallel::mclappy, but I got it
doMC/multicore too), if the library(tcltk) is loaded, R hangs when
trying to open a DB connection.
I got the same behaviour on two different computers, one dual-core,
and one 2 xeon quad-core.
Here's the code:
library(parallel)
library(RSQLite)
library(tcltk)
#unloadNamespace(&q...
2019 Apr 05
2
Deep Replicable Bug With AMD Threadripper MultiCore
The following program is whittled down from a much larger program that
always works on Intel, and always works on AMD's threadripper with
lapply but not mclappy. With mclapply on AMD, all processes go into
"suspend" mode and the program then hangs. This bug is replicable on an
AMD Ryzen Threadripper 2950X 16-Core Processor (128GB RAM), running
latest ubuntu 18.04. The R version 3.5.3 (2019-03-11) -- "Great Truth" ,
invoked with --van...
2019 Apr 05
0
Deep Replicable Bug With AMD Threadripper MultiCore
On 4 April 2019 at 17:28, ivo welch wrote:
| The following program is whittled down from a much larger program that
| always works on Intel, and always works on AMD's threadripper with
| lapply but not mclappy. With mclapply on AMD, all processes go into
| "suspend" mode and the program then hangs. This bug is replicable on an
| AMD Ryzen Threadripper 2950X 16-Core Processor (128GB RAM), running
| latest ubuntu 18.04. The R version 3.5.3 (2019-03-11) -- "Great Truth" ,
| invoked wi...
2019 Apr 13
3
SUGGESTION: Settings to disable forked processing in R, e.g. parallel::mclapply()
Hi Inaki,
> "Performant"... in terms of what. If the cost of copying the data
> predominates over the computation time, maybe you didn't need
> parallelization in the first place.
Performant in terms of speed. There's no copying in that example
using `mclapply` and so it is significantly faster than other
alternatives.
It is a very simple and contrived example, but