[Rd] reason for odd timings

[Steve Martin]

Just to add a bit more, stripping out most of your test shows that
there is one iteration (the 2nd one) that takes a lot longer than the
others because the sums() function gets bytecode compiled.

library(microbenchmark)

sums <- function(vv) {
  ss <- sum(vv^2)
  ss
}

sums2 <- compiler::cmpfun(sums)

x <- runif(100)

head(as.data.frame(microbenchmark(sums(x), sums2(x))))
          expr    time
1  sums(x)   29455
2  sums(x) 3683091
3 sums2(x)    7108
4  sums(x)    4305
5  sums(x)    2733
6  sums(x)    2797

The paragraph on JIT in the details of ?compiler::compile explains
that this is the default behavior.

Steve

On Fri, 21 Jan 2022 at 20:51, J C Nash <profjcnash using gmail.com> wrote:
>
> Occasionally I run some rather trivial timings to get an idea of what might
> be the best way to compute some quantities.
>
> The program below gave timings for sums of squares of 100 elements much greater
> than those for 1000, which seems surprising. Does anyone know the cause of this?
>
> This isn't holding up my work. Just causing some head scratching.
>
> JN
>
> > source("sstimer.R")
>  n        t(forloop) : ratio      t(sum) : ratio         t(crossprod)    all.equal
> 100      38719.15  :  1.766851   13421.12  :  0.6124391          21914.21        TRUE
> 1000     44722.71  :  20.98348   3093.94  :  1.451648    2131.33         TRUE
> 10000    420149.9  :  42.10269   27341.6  :  2.739867    9979.17         TRUE
> 1e+05    4070469  :  39.89473    343293.5  :  3.364625   102030.2        TRUE
> 1e+06    42293696  :  33.27684   3605866  :  2.837109    1270965         TRUE
> 1e+07    408123066  :  29.20882          35415106  :  2.534612   13972596        TRUE
> >
>
> # crossprod timer
> library(microbenchmark)
> suml<-function(vv) {
>     ss<-0.0
>     for (i in 1:length(vv)) {ss<-ss+vv[i]^2}
>     ss
> }
> sums<-function(vv) {
>   ss<-sum(vv^2)
>   ss
> }
> sumc<-function(vv) {
>   ss<-as.numeric(crossprod(vv))
>   ss
> }
> ll <- c(100, 1000, 10000, 100000, 1000000, 10000000)
> cat(" n  \t  t(forloop) : ratio \t  t(sum) : ratio \t t(crossprod) \t all.equal \n")
> for (nn in ll ){
>    set.seed(1234)
>    vv <- runif(nn)
>    tsuml<-microbenchmark(sl<-suml(vv), unit="us")
>    tsums<-microbenchmark(ss<-sums(vv), unit="us")
>    tsumc<-microbenchmark(sc<-sumc(vv), unit="us")
>    ml<-mean(tsuml$time)
>    ms<-mean(tsums$time)
>    mc<-mean(tsumc$time)
>    cat(nn,"\t",ml," : ",ml/mc,"\t",ms," : ",ms/mc,"\t",mc,"\t",all.equal(sl, ss, sc),"\n")
> }
>
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