Change forkTimeout() to use callr.

[krivit]

forkTimeout() uses parallel::mcparallel() to impose a hard time limit on a function call. Unfortunately, this mechanism is not available on Windows. In all evidence, the callr package does not have this limitation. It may be worthwhile to switch forkTimeout() to use it instead, assuming it does not impose too much of a speed penalty (and even if it does, use it on Windows only).

Background

From statnet/ergm-private#230, certain inputs can reliably hang ergm::is.inCH() via lpSolve::lp(), sending it into an infinite loop (or something indistinguishable from one):

library(lpSolve)
load(unz("lp_input.zip","lp_input.RData"))
lp(objective.in = c(-q, q),
             const.mat = rbind( c(q, -q), cbind(L, -L)),
             const.dir = "<=",
             const.rhs = c(1, rep(0, NROW(L)))
             )

Commits c2210babc72761ac81398e4d2212a672bc036ff0 and statnet/ergm@c417215 mostly neutralise this problem on Unix-alikes forkTimeout() to terminate the call if it takes too long and rerun with invariantly perturbed input, which seems to always fix the problem.

[krivit]

Benchmarks suggest that callr is much slower:

f <- function() 2+2
microbenchmark(callr=r(f), mcp={j<-mcparallel(f()); mccollect(j)[[1]]})

Unit: milliseconds
  expr        min         lq     mean   median         uq       max neval cld
 callr 145.128327 154.612408 165.7934 162.1669 176.778607 220.87554   100   b
   mcp   4.037625   5.281864   6.0387   5.7238   6.357726  10.86342   100  a 

[krivit]

On, the other hand, not restarting the R session every time is not as bad:

library(callr)
library(microbenchmark)
library(parallel)
f <- function() 2+2
rs <- r_session$new()
microbenchmark(r=r(f), rs={rs$call(f); rs$poll_process(-1); rs$read()$result}, mcp={j<-mcparallel(f()); mccollect(j)[[1]]})

Unit: milliseconds
 expr        min         lq       mean     median         uq        max neval cld
    r 145.869876 153.497698 161.952199 158.633111 168.728134 222.200421   100   c
   rs  17.170834  21.156948  24.776113  24.541950  28.002778  35.160594   100  b 
  mcp   1.980955   2.721543   2.998776   2.998492   3.285335   4.583885   100 a