[Rd] R_CheckUserInterrupt() can be a performance bottleneck within GUIs

[Tomas Kalibera]

On 12/18/24 01:19, Simon Urbanek wrote:
> It seems benign, but has implications since checking time is actually not a cheap operation: adding jus ta time check alone incurs a penalty of ca. 700% compared with the time it takes to call R_CheckUserInterrupt(). Generally, it makes no sense to check interrupts at every iteration - you'll find code like if (++i % 10000 == 0) R_CheckUserInterrupt(); in loops to make sure it's not called unnecessarily.

Yes, and worse yet, even the modulo operation has too high overhead in 
some loops (unless it is a power of two). It is faster to decrement and 
compare against zero.

It is the responsibility of the gui or application processing events 
that it doesn't do expensive operations on every call - that depends on 
what that application is doing and how expensive the processing is.

The frequency of calls to R_CheckUserInterrupt() should be tuned using 
base R without gui - if it were too high there, indeed the 
guis/applications couldn't do anything on their end. If anyone finds a 
loop in base R running standalone where the overhead is too high, the 
frequency can be adjusted - a bug report with reproducible example in 
that case would help.

Best
Tomas

> Cheers,
> Simon
>
>
>> On Dec 18, 2024, at 4:04 AM, Ben Bolker <bbolker using gmail.com> wrote:
>>
>>   This seems like a great idea. Would it help to escalate this to a post on R-bugzilla, so it is less likely to fall through the cracks?
>>
>> On 12/17/24 09:51, Jeroen Ooms wrote:
>>> A more generic solution would be for R to throttle calls to
>>> R_CheckUserInterrupt(), because it makes no sense to check 1000 times
>>> per second if a user has interrupted, but it is difficult for the
>>> caller to know when R_CheckUserInterrupt() has been last called, or do
>>> it regularly without over-doing it.
>>> Here is a simple patch: https://github.com/r-devel/r-svn/pull/125
>>> See also: https://stat.ethz.ch/pipermail/r-devel/2023-May/082597.html
>>> On Tue, Dec 17, 2024 at 10:47 AM Martin Becker
>>> <martin.becker using mx.uni-saarland.de> wrote:
>>>> tl;dr: R_CheckUserInterrupt() can be a performance bottleneck
>>>>          within GUIs. This also affects functions in the 'stats'
>>>>          package, which could be improved by changing the position
>>>>          of calls to R_CheckUserInterrupt().
>>>>
>>>>
>>>> Dear all,
>>>>
>>>> Recently I was puzzled because some code in a package under development,
>>>> which consisted almost entirely of a .Call() to a function written in C,
>>>> was running much slower within RStudio compared to R in a terminal. It
>>>> took me some time to identify the cause, so I thought I would share my
>>>> findings; perhaps they will be helpful to others.
>>>>
>>>> The performance drop was caused by R_CheckUserInterrupt(), which I call
>>>> (perhaps too often) in my C code. While calling R_CheckUserInterrupt()
>>>> seems to be quite cheap when running R or Rscript in a terminal, it is
>>>> more expensive when running R within a GUI, especially within RStudio,
>>>> as I noticed (but also, e.g., within R.app on MacOS). In fact, using a
>>>> GUI (especially RStudio) can change the cost of (frequent) calls to
>>>> R_CheckUserInterrupt() from negligible to critical (in real-world
>>>> applications). Significant performance drops are also visible for
>>>> functions in the 'stats' package, e.g., pwilcox().
>>>>
>>>> The following MWE (using Rcpp) illustrates the problem. Consider the
>>>> following code:
>>>>
>>>> ---
>>>>
>>>> library(Rcpp)
>>>> cppFunction('double nonsense(const int n, const int m, const int check) {
>>>>     int i, j;
>>>>     double result;
>>>>     for (i=0;i<n;i++) {
>>>>       if (check) R_CheckUserInterrupt();
>>>>       result = 1.;
>>>>       for (j=1;j<=m;j++) if (j%2) result *= j; else result /=j;
>>>>     }
>>>>     return(result);
>>>> }')
>>>>
>>>> tmp1 <- system.time(nonsense(1e8,10,0))[1]
>>>> tmp2 <- system.time(nonsense(1e8,10,1))[1]
>>>> cat("w/o check:",tmp1,"sec., with check:",tmp2,"sec.,
>>>> diff.:",tmp2-tmp1,"sec.\n")
>>>>
>>>> tmp3 <- system.time(pwilcox(rwilcox(1e5,40,60),40,60))[1]
>>>> cat("wilcox example:",tmp3,"sec.\n")
>>>>
>>>> ---
>>>>
>>>> Running this code when R (4.4.2) is started in a terminal window
>>>> produces the following measurements/output (Apple M1, MacOS 15.1.1):
>>>>
>>>>     w/o check: 0.525 sec., with check: 0.752 sec., diff.: 0.227 sec.
>>>>     wilcox example: 1.028 sec.
>>>>
>>>> Running the same code when R is used within R.app (1.81 (8462)
>>>> aarch64-apple-darwin20) on the same machine results in:
>>>>
>>>>     w/o check: 0.525 sec., with check: 1.683 sec., diff.: 1.158 sec.
>>>>     wilcox example: 2.13 sec.
>>>>
>>>> Running the same code when R is used within RStudio Desktop (2024.12.0
>>>> Build 467) on the same machine results in:
>>>>
>>>>     w/o check: 0.507 sec., with check: 22.905 sec., diff.: 22.398 sec.
>>>>     wilcox example: 29.686 sec.
>>>>
>>>> So, the performance drop is already remarkable for R.app, but really
>>>> huge for RStudio.
>>>>
>>>> Presumably, checking for user interrupts within a GUI is more involved
>>>> than within a terminal window, so there may not be much room for
>>>> improvement in R.app or RStudio (and I know that this list is not the
>>>> right place to suggest improvements for RStudio or to report unwanted
>>>> behaviour). However, it might be worth considering
>>>>
>>>> 1. an addition to the documentation in WRE (explaining that too many
>>>> calls to R_CheckUserInterrupt() can cause a performance bottleneck,
>>>> especially when the code is running within a GUI),
>>>> 2. check (and possibly change) the position of R_CheckUserInterrupt() in
>>>> some base R functions. For example, moving R_CheckUserInterrupt() from
>>>> cwilcox() to pwilcox() and qwilcox() in src/nmath/wilcox.c may lead to a
>>>> significant improvement (while still being feasible in terms of response
>>>> time).
>>>>
>>>> Best,
>>>> Martin
>>>>
>>>>
>>>> --
>>>> apl. Prof. Dr. Martin Becker, Akad. Oberrat
>>>> Lehrstab Statistik
>>>> Quantitative Methoden
>>>> Fakultät für Empirische Humanwissenschaften und Wirtschaftswissenschaft
>>>> Universität des Saarlandes
>>>> Campus C3 1, Raum 2.17
>>>> 66123 Saarbrücken
>>>> Deutschland
>>>>
>>>> ______________________________________________
>>>> R-devel using r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>> ______________________________________________
>>> R-devel using r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>> -- 
>> Dr. Benjamin Bolker
>> Professor, Mathematics & Statistics and Biology, McMaster University
>> Director, School of Computational Science and Engineering
>> * E-mail is sent at my convenience; I don't expect replies outside of working hours.
>>
>> ______________________________________________
>> R-devel using r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>
> ______________________________________________
> R-devel using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel