reason for odd timings

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 at 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")
}