> From: Tomas Kalibera <tomas.kalib...@gmail.com>
>
> Thanks for the report, I am working on a patch that will address this.
>
> I confirm there is a lot of potential for speedup. On my system,
>
> 'N=200000; x <- substring(paste(rep("A", N), collapse=""), 1:N, 1:N)'
>
> spends 96% time in checking if the string is ascii and 3% in strlen();
> if we take advantage of the pre-computed value in the ASCII bit, the
> speed up is about 40x.
The latest version of pqR (at pqR-project.org) has changes that
considerably speed up both this and other string operations.
Here's a test (both compiled with gcc 8.2.0 with -O3 on a Skylake processor).
R-3.5.2:
> N=200000; system.time(for (i in 1:100) r<-paste(rep("A",N),collapse=""))
user system elapsed
1.548 0.023 1.572
> system.time(for (i in 1:10) x<-substring(r,1:N,1:N))
user system elapsed
4.462 0.016 4.478
pqR-2019-02-19:
> N=200000; system.time(for (i in 1:100) r<-paste(rep("A",N),collapse=""))
user system elapsed
0.318 0.071 0.388
> system.time(for (i in 1:10) x<-substring(r,1:N,1:N))
user system elapsed
0.041 0.000 0.041
Some of this may be due to pqR's faster garbage collector - R Core
implementatons have a particular GC problem with strings, as explained at
https://radfordneal.wordpress.com/2018/11/29/faster-garbage-collection-in-pqr/
But there are also some specific improvements to string operations that
you might want to have a look at.
Radford Neal
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