Thanks for the help.
Attached are 3 files:
The simulation script as simulationR-R.txt
Rprof() output from R 3.1.3 as Rprof-3-1-3.txt
Rprof() output from R 3.5.1 as Rprof-3-5-1.txt
There is information about versions and system times at the top of the
simulation script. I had a student try it on her windows machine. She has R
version 3.4 installed. It performs the same as version 3.5, so whatever changes
to R account for the change in performance probably came before version 3.4
(and suggests it is not the OS).
I hope the script contains enough documentation that you can decipher it. There
are comments about what the algorithm is doing but also comments about things I
have done to try to isolate the problem (deleting stuff and moving things
around, which by the way makes nonsense of the simulation itself, but that is
not an issue here).
It uses the igraph package, but I re-arranged things such that I am pretty sure
that is not the problem. I realized just now I could get rid of the igraph
stuff altogether for debugging purposes if that would help. Let me know about
that.
Thanks for your help. I hope you can track it down, because this kind of speed
degradation make me really hesitate to upgrade.
Robin Cowan
###### ########
#some system times
##############
#R version 3.5.1
# > system.time(source("simulationR-R.R"))
# user system elapsed
# 77.300 0.570 77.389
# > sessionInfo()
# R version 3.5.1 (2018-07-02)
# Platform: x86_64-apple-darwin15.6.0 (64-bit)
# Running under: macOS Sierra 10.12.6
# Matrix products: default
# BLAS:
/Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
# LAPACK:
/Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
# locale:
# [1] C
# attached base packages:
# [1] stats graphics grDevices utils datasets methods base
# other attached packages:
# [1] igraph_1.2.2
# loaded via a namespace (and not attached):
# [1] compiler_3.5.1 magrittr_1.5 pkgconfig_2.0.2
#########
## 3.1.3
# user system elapsed
# 0.648 0.005 0.648
# > sessionInfo()
# R version 3.1.3 Patched (2015-04-21 r70342)
# Platform: x86_64-apple-darwin10.8.0 (64-bit)
# Running under: OS X 10.9.5 (Mavericks)
# locale:
# [1] C
# attached base packages:
# [1] stats graphics grDevices utils datasets methods base
# other attached packages:
# [1] igraph_0.7.1
#########
### from a colleague:
# R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
# Platform: x86_64-w64-mingw32/x64 (64-bit)
# user  system elapsedÂ
#Â 72.94 Â Â Â 0.02 Â Â 72.99Â
######################
### starts here
######################
#### compiling or not compiling doesn't change the relative speeds of the two
versions
# library(compiler)
# enableJIT(3)
library(igraph)
#### a function used later
PlaytheGame=function(i11=i,opp1=opp){
P=sum(PayoffMatrix[strategy[i11],strategy[opp1]])
return(P/length(opp1))
} # Play the Game
#### set some parameters (this is a game theory simulation, played on a
network)
### payoff matrix for the game
b=1.5
PayoffMatrix<-matrix(c(1,0,b,0),nrow=2,ncol=2,byrow=TRUE)
#each player plays Total Rounds of the game
TotalRounds<-100
## how often to write data
writefreq=20
#number of agents
num<-100
# density of the network
dens<-0.10
avgdeg<-dens*num/2
# create filenames to write output into
filename=paste("R-R")
filename2=paste("moran,R-R,g")
filename3=paste("moran,R-R,gk")
# delete old datafiles
if (file.exists(filename)) file.remove(filename)
if (file.exists(filename2)) file.remove(filename2)
if (file.exists(filename3)) file.remove(filename3)
# how many opponents to play at each round
numoppon<-1
### create the networks to play the game on
# notice that these are here to test the speed of the simulation
# in principle they should be inside the repetitions loop.
# I moved them here to see if igraph is causing the problem,
# igraph is only called here now instead of each time the experiment repeats.
# Below you can see these commented out. You can check the effects of igraph
by uncommenting them below.
# I concluded the problem is not igraph. Sadly.
# create the networks to play on
repeat{
g<-erdos.renyi.game(num,dens)
if(is.connected(g)){break}
} # repeat
neigh<-neighborhood(g,order=1)
repeat{
gk<-erdos.renyi.game(num,dens)
if(is.connected(gk)){break}
} # repeat
neighGk<-neighborhood(gk,order=1)
distmatrix<-1/(shortest.paths(g))
diag(distmatrix)<-0
distmatrix2<-1/(shortest.paths(gk))
diag(distmatrix2)<-0
###Here we repeat the experiment 5 times (for the actual project we are
working on we repeat it 100 times)
for(reps in 1:5){
### initialize players' strategies
strategy<-sample(c(1,2),num,replace=TRUE)
oldstrategy=strategy
### set aggregated payoffs to zero for each player
payoff<-rep(0,num)
########
# for the real thing we make new networks for each repetition
########
# repeat{
# g<-erdos.renyi.game(num,dens)
# if(is.connected(g)){break}
# } # repeat
# neigh<-neighborhood(g,order=1)
# repeat{
# gk<-erdos.renyi.game(num,dens)
# if(is.connected(gk)){break}
# } # repeat
# neighGk<-neighborhood(gk,order=1)
# distmatrix<-1/(shortest.paths(g))
# diag(distmatrix)<-0
# distmatrix2<-1/(shortest.paths(gk))
# diag(distmatrix2)<-0
###################
############# end of the igraph stuff that should be done each time.
####
# start time here
####
for(r in 1:TotalRounds){
newstrat=numeric()
PayVector=numeric()
## for each player, make him play the game
for (i in 1:num){
######## I tried doing this not using a loop, using apply, but it made no
difference
### he plays against his neighbours
n1=neigh[[i]][-1]
nopp=max(length(n1),numoppon)
opp=n1[1]
if (length(n1)>1){
opp=sample(n1,nopp)}
### get a payoff from each opponent played and add to payoffs
PayVector[i]=PlaytheGame(i,opp)
}# i loop
#### after everyone has played, pick one guy and revise his strategy
chosen.one<-sample(1:num,1)
#strategy[chosen.one]=ImitateRichestNeighbor(chosen.one,neighGk[[chosen.one]])
###### for the sake of debugging just change strategy randomly
strategy[chosen.one]<-sample(c(0,1),1)
#update payoff records
payoff=payoff+PayVector
### this write statement is not relevant to debugging for speed it seems
#if((r %% writefreq)==0){
#write(file=filename,ncolumns=8,sep=",",x=c(r,sum(strategy==1),mean(payoff),sd(payoff),min(payoff),max(payoff),strategy[which.min(payoff)],strategy[which.max(payoff)]),append=T)
#}
### a single run of the experiment ends ends here
} #r loop
##############
### what follows has been commented out to see if the bottleneck was there
# sadly, that didn't help.
##############
# if((sum(strategy)==num) | (sum(strategy)==(num*2))){
# morant1="allthesame"
# }else{morant1=Moran.I(strategy,distmatrix)
# }
# moranpayoff<-Moran.I(payoff,distmatrix)
# as.character(moranpayoff)
# if((sum(strategy)==num) | (sum(strategy)==(num*2))){
# moran2t1="allthesame"
# }else{moran2t1=Moran.I(strategy,distmatrix)
# }
# moranpayoff2<-Moran.I(payoff,distmatrix2)
# as.character(moranpayoff2)
#write.table(x=c(as.character(morant1),as.character(moranpayoff)),file=filename2,sep=",",append=T,col.names=F)
#write.table(x=c(as.character(moran2t1),as.character(moranpayoff2)),file=filename3,sep=",",append=T,col.names=F)
print(c("done ",reps))
#### now the reptetition is done.
} #reps loop
$by.self
self.time self.pct total.time total.pct
"eval" 0.28 36.84 0.76 100.00
"sample.int" 0.24 31.58 0.24 31.58
"PlaytheGame" 0.12 15.79 0.16 21.05
"sum" 0.04 5.26 0.04 5.26
"<Anonymous>" 0.02 2.63 0.02 2.63
"length" 0.02 2.63 0.02 2.63
"max" 0.02 2.63 0.02 2.63
"namespaceImportFrom" 0.02 2.63 0.02 2.63
$by.total
total.time total.pct self.time self.pct
"eval" 0.76 100.00 0.28 36.84
"source" 0.76 100.00 0.00 0.00
"withVisible" 0.76 100.00 0.00 0.00
"sample.int" 0.24 31.58 0.24 31.58
"sample" 0.24 31.58 0.00 0.00
"PlaytheGame" 0.16 21.05 0.12 15.79
"sum" 0.04 5.26 0.04 5.26
"doTryCatch" 0.04 5.26 0.00 0.00
"library" 0.04 5.26 0.00 0.00
"loadNamespace" 0.04 5.26 0.00 0.00
"try" 0.04 5.26 0.00 0.00
"tryCatch" 0.04 5.26 0.00 0.00
"tryCatchList" 0.04 5.26 0.00 0.00
"tryCatchOne" 0.04 5.26 0.00 0.00
"<Anonymous>" 0.02 2.63 0.02 2.63
"length" 0.02 2.63 0.02 2.63
"max" 0.02 2.63 0.02 2.63
"namespaceImportFrom" 0.02 2.63 0.02 2.63
".Call" 0.02 2.63 0.00 0.00
"fun" 0.02 2.63 0.00 0.00
"namespaceImport" 0.02 2.63 0.00 0.00
"runHook" 0.02 2.63 0.00 0.00
$sample.interval
[1] 0.02
$sampling.time
[1] 0.76
$by.self
self.time self.pct total.time total.pct
"as.list" 4.28 6.02 6.12 8.61
"split_chain" 3.94 5.55 19.94 28.07
"eval" 3.52 4.95 71.04 100.00
"lapply" 3.40 4.79 14.86 20.92
"%>%" 3.08 4.34 42.82 60.28
"unique" 2.78 3.91 5.24 7.38
"vapply" 2.38 3.35 4.68 6.59
"FUN" 2.04 2.87 10.82 15.23
"length" 1.96 2.76 1.96 2.76
"match.call" 1.90 2.67 3.50 4.93
"[.igraph.vs" 1.76 2.48 69.50 97.83
"unique.default" 1.70 2.39 2.12 2.98
"as.list.default" 1.62 2.28 1.62 2.28
"sapply" 1.50 2.11 10.36 14.58
"rev" 1.32 1.86 2.22 3.12
"stopifnot" 1.14 1.60 7.34 10.33
"withCallingHandlers" 1.04 1.46 4.46 6.28
"withVisible" 1.02 1.44 71.04 100.00
"match.fun" 1.02 1.44 1.16 1.63
"doTryCatch" 0.98 1.38 1.92 2.70
"is_pipe" 0.94 1.32 0.94 1.32
"wrap_function" 0.84 1.18 5.60 7.88
"is_dollar" 0.84 1.18 0.84 1.18
"sys.call" 0.82 1.15 1.00 1.41
"prepare_first" 0.76 1.07 3.44 4.84
"rev.default" 0.76 1.07 0.90 1.27
"parse_op_args" 0.68 0.96 45.64 64.25
"%in%" 0.66 0.93 0.80 1.13
"alist" 0.64 0.90 2.52 3.55
"simplify2array" 0.62 0.87 5.14 7.24
"tryCatch" 0.60 0.84 3.34 4.70
"$" 0.60 0.84 0.60 0.84
"add_vses_graph_ref" 0.58 0.82 9.50 13.37
"freduce" 0.58 0.82 7.92 11.15
"sys.parent" 0.58 0.82 0.58 0.82
"c" 0.56 0.79 54.04 76.07
"simple_vs_index" 0.54 0.76 0.82 1.15
"is_funexpr" 0.54 0.76 0.56 0.79
"is_igraph" 0.52 0.73 1.32 1.86
"[[" 0.48 0.68 0.48 0.68
"new.env" 0.48 0.68 0.48 0.68
"unlist" 0.48 0.68 0.48 0.68
"is_tee" 0.46 0.65 0.46 0.65
"do_call" 0.44 0.62 54.74 77.06
"as.pairlist" 0.44 0.62 2.96 4.17
"is_parenthesized" 0.44 0.62 0.54 0.76
"is.factor" 0.42 0.59 0.42 0.59
"[" 0.40 0.56 69.90 98.40
"drop_null" 0.40 0.56 4.04 5.69
"parent.frame" 0.40 0.56 0.40 0.56
"graph_version" 0.38 0.53 7.72 10.87
"is_first" 0.38 0.53 5.26 7.40
"PlaytheGame" 0.38 0.53 0.44 0.62
"tryCatchList" 0.36 0.51 2.60 3.66
"make_call" 0.36 0.51 0.40 0.56
"isFALSE" 0.34 0.48 0.52 0.73
"is.call" 0.34 0.48 0.34 0.48
"lengths" 0.34 0.48 0.34 0.48
"as.vector" 0.32 0.45 0.32 0.45
"tryCatchOne" 0.30 0.42 2.22 3.12
"sys.function" 0.30 0.42 0.70 0.99
"lazy_dots" 0.30 0.42 0.40 0.56
"list" 0.30 0.42 0.30 0.42
"c.igraph.vs" 0.28 0.39 53.62 75.48
"_fseq" 0.28 0.39 8.20 11.54
"any" 0.28 0.39 0.28 0.39
"is_placeholder" 0.28 0.39 0.28 0.39
"logical" 0.28 0.39 0.28 0.39
"get_vs_ref" 0.24 0.34 4.80 6.76
"%&&%" 0.24 0.34 1.08 1.52
"...elt" 0.24 0.34 0.70 0.99
"get_vs_graph" 0.24 0.34 0.36 0.51
"as.lazy" 0.24 0.34 0.26 0.37
"warn_version" 0.22 0.31 7.94 11.18
"create_op_result" 0.20 0.28 6.88 9.68
"sample.int" 0.20 0.28 0.32 0.45
"is_function" 0.20 0.28 0.24 0.34
"all" 0.20 0.28 0.20 0.28
"is.function" 0.18 0.25 0.18 0.25
"is.na" 0.18 0.25 0.18 0.25
"is_compound_pipe" 0.18 0.25 0.18 0.25
"function_list[[i]]" 0.16 0.23 3.88 5.46
"vertex_attr" 0.16 0.23 0.64 0.90
"environment" 0.16 0.23 0.16 0.23
"is.lazy_dots" 0.16 0.23 0.16 0.23
"make_weak_ref" 0.16 0.23 0.16 0.23
"lazy_eval" 0.14 0.20 2.68 3.77
"as.call" 0.14 0.20 0.14 0.20
"attr" 0.14 0.20 0.14 0.20
"function_list[[k]]" 0.12 0.17 3.10 4.36
"class" 0.12 0.17 0.12 0.17
"unclass" 0.12 0.17 0.12 0.17
"get_graph_id" 0.10 0.14 3.96 5.57
"vertex.attributes" 0.10 0.14 0.28 0.39
"weak_ref_key" 0.10 0.14 0.10 0.14
"parse_vs_op_args" 0.08 0.11 45.74 64.39
"address" 0.08 0.11 0.08 0.11
"max" 0.06 0.08 0.06 0.08
"sample" 0.04 0.06 33.98 47.83
"anyNA" 0.04 0.06 0.04 0.06
"is.list" 0.04 0.06 0.04 0.06
"is.pairlist" 0.04 0.06 0.04 0.06
"names" 0.04 0.06 0.04 0.06
"loadNamespace" 0.02 0.03 0.04 0.06
"-" 0.02 0.03 0.02 0.03
"<=" 0.02 0.03 0.02 0.03
"as.lazy.lazy" 0.02 0.03 0.02 0.03
"baseenv" 0.02 0.03 0.02 0.03
"class<-" 0.02 0.03 0.02 0.03
"cmp" 0.02 0.03 0.02 0.03
"conditionMessage" 0.02 0.03 0.02 0.03
"is.null" 0.02 0.03 0.02 0.03
"lazyLoadDBfetch" 0.02 0.03 0.02 0.03
"nargs" 0.02 0.03 0.02 0.03
"paste" 0.02 0.03 0.02 0.03
"print.default" 0.02 0.03 0.02 0.03
"sum" 0.02 0.03 0.02 0.03
"tolower" 0.02 0.03 0.02 0.03
$by.total
total.time total.pct self.time self.pct
"eval" 71.04 100.00 3.52 4.95
"withVisible" 71.04 100.00 1.02 1.44
"source" 71.04 100.00 0.00 0.00
"[" 69.90 98.40 0.40 0.56
"[.igraph.vs" 69.50 97.83 1.76 2.48
"do_call" 54.74 77.06 0.44 0.62
"c" 54.04 76.07 0.56 0.79
"c.igraph.vs" 53.62 75.48 0.28 0.39
"parse_vs_op_args" 45.74 64.39 0.08 0.11
"parse_op_args" 45.64 64.25 0.68 0.96
"%>%" 42.82 60.28 3.08 4.34
"sample" 33.98 47.83 0.04 0.06
"split_chain" 19.94 28.07 3.94 5.55
"lapply" 14.86 20.92 3.40 4.79
"FUN" 10.82 15.23 2.04 2.87
"sapply" 10.36 14.58 1.50 2.11
"add_vses_graph_ref" 9.50 13.37 0.58 0.82
"_fseq" 8.20 11.54 0.28 0.39
"warn_version" 7.94 11.18 0.22 0.31
"freduce" 7.92 11.15 0.58 0.82
"graph_version" 7.72 10.87 0.38 0.53
"stopifnot" 7.34 10.33 1.14 1.60
"create_op_result" 6.88 9.68 0.20 0.28
"as.list" 6.12 8.61 4.28 6.02
"wrap_function" 5.60 7.88 0.84 1.18
"is_first" 5.26 7.40 0.38 0.53
"unique" 5.24 7.38 2.78 3.91
"simplify2array" 5.14 7.24 0.62 0.87
"get_vs_ref" 4.80 6.76 0.24 0.34
"vapply" 4.68 6.59 2.38 3.35
"withCallingHandlers" 4.46 6.28 1.04 1.46
"drop_null" 4.04 5.69 0.40 0.56
"get_graph_id" 3.96 5.57 0.10 0.14
"function_list[[i]]" 3.88 5.46 0.16 0.23
"match.call" 3.50 4.93 1.90 2.67
"prepare_first" 3.44 4.84 0.76 1.07
"tryCatch" 3.34 4.70 0.60 0.84
"function_list[[k]]" 3.10 4.36 0.12 0.17
"as.pairlist" 2.96 4.17 0.44 0.62
"lazy_eval" 2.68 3.77 0.14 0.20
"tryCatchList" 2.60 3.66 0.36 0.51
"alist" 2.52 3.55 0.64 0.90
"rev" 2.22 3.12 1.32 1.86
"tryCatchOne" 2.22 3.12 0.30 0.42
"unique.default" 2.12 2.98 1.70 2.39
"length" 1.96 2.76 1.96 2.76
"doTryCatch" 1.92 2.70 0.98 1.38
"as.list.default" 1.62 2.28 1.62 2.28
"is_igraph" 1.32 1.86 0.52 0.73
"match.fun" 1.16 1.63 1.02 1.44
"%&&%" 1.08 1.52 0.24 0.34
"sys.call" 1.00 1.41 0.82 1.15
"is_pipe" 0.94 1.32 0.94 1.32
"rev.default" 0.90 1.27 0.76 1.07
"is_dollar" 0.84 1.18 0.84 1.18
"simple_vs_index" 0.82 1.15 0.54 0.76
"%in%" 0.80 1.13 0.66 0.93
"sys.function" 0.70 0.99 0.30 0.42
"...elt" 0.70 0.99 0.24 0.34
"vertex_attr" 0.64 0.90 0.16 0.23
"$" 0.60 0.84 0.60 0.84
"sys.parent" 0.58 0.82 0.58 0.82
"is_funexpr" 0.56 0.79 0.54 0.76
"is_parenthesized" 0.54 0.76 0.44 0.62
"isFALSE" 0.52 0.73 0.34 0.48
"[[" 0.48 0.68 0.48 0.68
"new.env" 0.48 0.68 0.48 0.68
"unlist" 0.48 0.68 0.48 0.68
"is_tee" 0.46 0.65 0.46 0.65
"PlaytheGame" 0.44 0.62 0.38 0.53
"is.factor" 0.42 0.59 0.42 0.59
"parent.frame" 0.40 0.56 0.40 0.56
"make_call" 0.40 0.56 0.36 0.51
"lazy_dots" 0.40 0.56 0.30 0.42
"get_vs_graph" 0.36 0.51 0.24 0.34
"is.call" 0.34 0.48 0.34 0.48
"lengths" 0.34 0.48 0.34 0.48
"as.vector" 0.32 0.45 0.32 0.45
"sample.int" 0.32 0.45 0.20 0.28
"list" 0.30 0.42 0.30 0.42
"any" 0.28 0.39 0.28 0.39
"is_placeholder" 0.28 0.39 0.28 0.39
"logical" 0.28 0.39 0.28 0.39
"vertex.attributes" 0.28 0.39 0.10 0.14
"as.lazy" 0.26 0.37 0.24 0.34
"is_function" 0.24 0.34 0.20 0.28
"all" 0.20 0.28 0.20 0.28
"is.function" 0.18 0.25 0.18 0.25
"is.na" 0.18 0.25 0.18 0.25
"is_compound_pipe" 0.18 0.25 0.18 0.25
"environment" 0.16 0.23 0.16 0.23
"is.lazy_dots" 0.16 0.23 0.16 0.23
"make_weak_ref" 0.16 0.23 0.16 0.23
"as.call" 0.14 0.20 0.14 0.20
"attr" 0.14 0.20 0.14 0.20
"class" 0.12 0.17 0.12 0.17
"unclass" 0.12 0.17 0.12 0.17
"weak_ref_key" 0.10 0.14 0.10 0.14
"address" 0.08 0.11 0.08 0.11
"max" 0.06 0.08 0.06 0.08
"library" 0.06 0.08 0.00 0.00
"anyNA" 0.04 0.06 0.04 0.06
"is.list" 0.04 0.06 0.04 0.06
"is.pairlist" 0.04 0.06 0.04 0.06
"names" 0.04 0.06 0.04 0.06
"loadNamespace" 0.04 0.06 0.02 0.03
"-" 0.02 0.03 0.02 0.03
"<=" 0.02 0.03 0.02 0.03
"as.lazy.lazy" 0.02 0.03 0.02 0.03
"baseenv" 0.02 0.03 0.02 0.03
"class<-" 0.02 0.03 0.02 0.03
"cmp" 0.02 0.03 0.02 0.03
"conditionMessage" 0.02 0.03 0.02 0.03
"is.null" 0.02 0.03 0.02 0.03
"lazyLoadDBfetch" 0.02 0.03 0.02 0.03
"nargs" 0.02 0.03 0.02 0.03
"paste" 0.02 0.03 0.02 0.03
"print.default" 0.02 0.03 0.02 0.03
"sum" 0.02 0.03 0.02 0.03
"tolower" 0.02 0.03 0.02 0.03
"asNamespace" 0.02 0.03 0.00 0.00
"cb$putconst" 0.02 0.03 0.00 0.00
"checkConflicts" 0.02 0.03 0.00 0.00
"cmpCall" 0.02 0.03 0.00 0.00
"cmpCallArgs" 0.02 0.03 0.00 0.00
"cmpCallSymFun" 0.02 0.03 0.00 0.00
"cmpRepeatBody" 0.02 0.03 0.00 0.00
"cmpSymbolAssign" 0.02 0.03 0.00 0.00
"compile" 0.02 0.03 0.00 0.00
"compiler:::tryCompile" 0.02 0.03 0.00 0.00
"doWithOneRestart" 0.02 0.03 0.00 0.00
"erdos.renyi.game" 0.02 0.03 0.00 0.00
"genCode" 0.02 0.03 0.00 0.00
"h" 0.02 0.03 0.00 0.00
"igraph.match.arg" 0.02 0.03 0.00 0.00
"message" 0.02 0.03 0.00 0.00
"namespaceImportFrom" 0.02 0.03 0.00 0.00
"packageStartupMessage" 0.02 0.03 0.00 0.00
"print" 0.02 0.03 0.00 0.00
"registerS3methods" 0.02 0.03 0.00 0.00
"signalCondition" 0.02 0.03 0.00 0.00
"tryInline" 0.02 0.03 0.00 0.00
"withOneRestart" 0.02 0.03 0.00 0.00
"withRestarts" 0.02 0.03 0.00 0.00
$sample.interval
[1] 0.02
$sampling.time
[1] 71.04
>
> On 13 Dec 2018, at 14:37, Martin Maechler <maech...@stat.math.ethz.ch> wrote:
>
>>>>>> Peter Dalgaard
>>>>>> on Wed, 12 Dec 2018 22:12:34 +0100 writes:
>
>> I don't think there has been anything mentioned about slowdowns of that
>> magnitude, but it's been 3.5 years since 3.1.3.
>> Would it be possible to narrow down what kind of code has become slow?
>
>> Since the OS version is different, I assume the first timing is historical
>> and not easily redone, but if it is now using like 70 times as long as
>> before, chances are that it is spending 69/70 of the time in the same few
>> places.
>
>> One generic frequent cause of grief with simulations is to keep onto the
>> fitted models in entirety, including model frames etc., causing massive
>> memory build-up.
>
>> -pd
>
> If the simulationR-R.R script is basically reproducible
> (i.e. does not use data or other resources that only exist on
> your computer), it would probably be useful if you "donated"
> it to the R project by making it publicly available. Some of
> us do have many old R versions still running, and could quickly
> try and see...
>
> Martin Maechler (not a Mac user though)
>
>>> On 12 Dec 2018, at 17:39 , Cowan, R (MERIT)
>>> <r.co...@maastrichtuniversity.nl> wrote:
>>>
>>> I am running a small simulation, and getting very different run times when
>>> I use different versions of R.
>>> Two set-ups using the same machine (MacBook Pro 2013 vintage)
>>>
>>> 1. R version 3.1.3 running on system OS X 10.9.5
>>>
>>>> system.time(source("simulationR-R.R"))
>>>
>>> user system elapsed
>>> 3.890 0.061 3.965
>>>
>>> Compared to
>>>
>>> 2. R version 3.5.1 running on system OS X 10.12.6
>>>
>>>> system.time(source("simulationR-R.R"))
>>>
>>> user system elapsed
>>> 277.924 2.087 280.841
>>>
>>> The source code is identical. This is a pretty big difference running the
>>> same code on the same hardware.
>>> Before submitting the code, is this a known issue?
>>>
>>>
>>> Thanks,
>>> Robin Cowan
>>> _______________________________________________
>>> R-SIG-Mac mailing list
>>> R-SIG-Mac@r-project.org
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mac
>
>> --
>> Peter Dalgaard, Professor,
>> Center for Statistics, Copenhagen Business School
>> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
>> Phone: (+45)38153501
>> Office: A 4.23
>> Email: pd....@cbs.dk Priv: pda...@gmail.com
>
>
>
_______________________________________________
R-SIG-Mac mailing list
R-SIG-Mac@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-mac
