Performance of `rcpp_get_unique_values()`
Closed this issue · 6 comments
Nowosad commented
I tried two computers while working on #87. The first one is a laptop with i5 and the second one is a desktop with a much better i7. The performance of rcpp_get_unique_values(), however, is about 10 times better on a laptop. Can you think why is that? @marcosci @mhesselbarth @bitbacchus
laptop with i5
library(landscapemetrics)
library(raster)
#> Loading required package: sp
bench::mark(landscapemetrics:::rcpp_get_unique_values(as.matrix(augusta_nlcd)))
#> # A tibble: 1 x 10
#> expression min mean median max `itr/sec` mem_alloc n_gc n_itr
#> <chr> <bch:> <bch:> <bch:> <bch> <dbl> <bch:byt> <dbl> <int>
#> 1 landscape… 4.18ms 4.54ms 4.57ms 5.6ms 220. 4.72MB 3 104
#> # … with 1 more variable: total_time <bch:tm>Created on 2019-04-19 by the reprex package (v0.2.1)
Session info
devtools::session_info()
#> ─ Session info ──────────────────────────────────────────────────────────
#> setting value
#> version R version 3.5.3 (2019-03-11)
#> os Fedora 29 (Workstation Edition)
#> system x86_64, linux-gnu
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Warsaw
#> date 2019-04-19
#>
#> ─ Packages ──────────────────────────────────────────────────────────────
#> package * version date lib
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#>
#> [1] /home/jn/R/x86_64-redhat-linux-gnu-library/3.5
#> [2] /usr/lib64/R/library
#> [3] /usr/share/R/librarydesktop with i7
library(landscapemetrics)
library(raster)
#> Loading required package: sp
bench::mark(landscapemetrics:::rcpp_get_unique_values(as.matrix(augusta_nlcd)))
#> # A tibble: 1 x 10
#> expression min mean median max `itr/sec` mem_alloc n_gc n_itr
#> <chr> <bch:> <bch:> <bch:> <bch:> <dbl> <bch:byt> <dbl> <int>
#> 1 landscape… 37.3ms 37.9ms 37.7ms 39.2ms 26.4 4.72MB 1 13
#> # … with 1 more variable: total_time <bch:tm>Created on 2019-04-19 by the reprex package (v0.2.1)
Session info
devtools::session_info()
#> ─ Session info ──────────────────────────────────────────────────────────
#> setting value
#> version R version 3.5.3 (2019-03-11)
#> os Fedora 29 (Workstation Edition)
#> system x86_64, linux-gnu
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Warsaw
#> date 2019-04-19
#>
#> ─ Packages ──────────────────────────────────────────────────────────────
#> package * version date lib
#> assertthat 0.2.1 2019-03-21 [1]
#> backports 1.1.3 2018-12-14 [1]
#> bench 1.0.1 2018-06-06 [1]
#> callr 3.2.0 2019-03-15 [1]
#> cli 1.1.0 2019-03-19 [1]
#> codetools 0.2-16 2018-12-24 [2]
#> crayon 1.3.4 2017-09-16 [1]
#> desc 1.2.0 2018-05-01 [1]
#> devtools 2.0.1 2018-10-26 [1]
#> digest 0.6.18 2018-10-10 [1]
#> evaluate 0.13 2019-02-12 [1]
#> fansi 0.4.0 2018-10-05 [1]
#> fs 1.2.7 2019-03-19 [1]
#> glue 1.3.1 2019-03-12 [1]
#> highr 0.8 2019-03-20 [1]
#> htmltools 0.3.6 2017-04-28 [1]
#> knitr 1.22 2019-03-08 [1]
#> landscapemetrics * 1.1 2019-04-19 [1]
#> lattice 0.20-38 2018-11-04 [2]
#> magrittr 1.5 2014-11-22 [1]
#> memoise 1.1.0 2017-04-21 [1]
#> pillar 1.3.1 2018-12-15 [1]
#> pkgbuild 1.0.3 2019-03-20 [1]
#> pkgconfig 2.0.2 2018-08-16 [1]
#> pkgload 1.0.2 2018-10-29 [1]
#> prettyunits 1.0.2 2015-07-13 [1]
#> processx 3.3.0 2019-03-10 [1]
#> profmem 0.5.0 2018-01-30 [1]
#> ps 1.3.0 2018-12-21 [1]
#> R6 2.4.0 2019-02-14 [1]
#> raster * 2.9-2 2019-04-12 [1]
#> Rcpp 1.0.1 2019-03-17 [1]
#> remotes 2.0.4 2019-04-10 [1]
#> rlang 0.3.4 2019-04-07 [1]
#> rmarkdown 1.12 2019-03-14 [1]
#> rprojroot 1.3-2 2018-01-03 [1]
#> sessioninfo 1.1.1 2018-11-05 [1]
#> sp * 1.3-1 2018-06-05 [1]
#> stringi 1.4.3 2019-03-12 [1]
#> stringr 1.4.0 2019-02-10 [1]
#> testthat 2.0.1 2018-10-13 [1]
#> tibble 2.1.1 2019-03-16 [1]
#> usethis 1.4.0 2018-08-14 [1]
#> utf8 1.1.4 2018-05-24 [1]
#> withr 2.1.2 2018-03-15 [1]
#> xfun 0.5 2019-02-20 [1]
#> yaml 2.2.0 2018-07-25 [1]
#> source
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#> Github (rspatial/raster@81060dc)
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#> [1] /home/jn/R/x86_64-redhat-linux-gnu-library/3.5
#> [2] /usr/lib64/R/library
#> [3] /usr/share/R/librarybitbacchus commented
Hm, this sounds weird. Can you try again with manually setting the number of iterations:
bench::mark(landscapemetrics:::rcpp_get_unique_values(as.matrix(augusta_nlcd)), iterations = 10000)
# A tibble: 1 x 14
expression min mean median max `itr/sec` mem_alloc n_gc n_itr total_time result memory time gc
<chr> <bch:t> <bch:t> <bch:t> <bch:t> <dbl> <bch:byt> <dbl> <int> <bch:tm> <list> <list> <lis> <list>
1 landscapemetrics:::rc… 2.63ms 2.97ms 2.97ms 4.31ms 337. 1.14MB 385 9615 28.6s <int … <Rprofm… <bch… <tibble…Are the versions of gcc the same? Do both PC have SSD disks?
marcosci commented
Do you know what's the default number of iterations there Jakub? Could that be a source for this (maybe it was just too few iterations)?
Nowosad commented
laptop with i5
library(landscapemetrics)
library(raster)
#> Loading required package: sp
bench::mark(landscapemetrics:::rcpp_get_unique_values(as.matrix(augusta_nlcd)), iterations = 1000)
#> # A tibble: 1 x 10
#> expression min mean median max `itr/sec` mem_alloc n_gc n_itr
#> <chr> <bch:> <bch:> <bch:> <bch:> <dbl> <bch:byt> <dbl> <int>
#> 1 landscape… 4.14ms 4.79ms 4.63ms 6.63ms 209. 4.72MB 36 964
#> # … with 1 more variable: total_time <bch:tm>Created on 2019-04-24 by the reprex package (v0.2.1)
desktop with i7
library(landscapemetrics)
library(raster)
#> Loading required package: sp
bench::mark(landscapemetrics:::rcpp_get_unique_values(as.matrix(augusta_nlcd)), iterations = 1000)
#> # A tibble: 1 x 10
#> expression min mean median max `itr/sec` mem_alloc n_gc n_itr
#> <chr> <bch:> <bch:> <bch:> <bch:> <dbl> <bch:byt> <dbl> <int>
#> 1 landscape… 36.6ms 37.6ms 37.3ms 41.2ms 26.6 4.72MB 36 964
#> # … with 1 more variable: total_time <bch:tm>Created on 2019-04-24 by the reprex package (v0.2.1)
gcc on both computers: gcc (GCC) 8.3.1 20190223 (Red Hat 8.3.1-2). Also - both computer have SSD disks.
It is not a huge problem for me, however It would be nice to find the reason for this difference...
bitbacchus commented
But is it actually related to rcpp_get_unique_values?
Is
bench::mark(raster::unique(as.matrix(augusta_nlcd)), iterations = 1000)also faster on the i5 laptop?
Nowosad commented
laptop with i5
library(landscapemetrics)
library(raster)
#> Loading required package: sp
bench::mark(landscapemetrics:::rcpp_get_unique_values(as.matrix(augusta_nlcd)), iterations = 1000)
#> # A tibble: 1 x 10
#> expression min mean median max `itr/sec` mem_alloc n_gc n_itr
#> <chr> <bch:> <bch:> <bch:> <bch:> <dbl> <bch:byt> <dbl> <int>
#> 1 landscape… 4.16ms 4.95ms 4.8ms 8.32ms 202. 4.72MB 36 964
#> # … with 1 more variable: total_time <bch:tm>
bench::mark(raster::unique(as.matrix(augusta_nlcd)), iterations = 1000)
#> # A tibble: 1 x 10
#> expression min mean median max `itr/sec` mem_alloc n_gc n_itr
#> <chr> <bch:> <bch> <bch:> <bch:> <dbl> <bch:byt> <dbl> <int>
#> 1 raster::u… 3.97ms 5.1ms 4.7ms 10.6ms 196. 5.79MB 232 768
#> # … with 1 more variable: total_time <bch:tm>Created on 2019-04-24 by the reprex package (v0.2.1)
desktop with i7
library(landscapemetrics)
library(raster)
#> Loading required package: sp
bench::mark(landscapemetrics:::rcpp_get_unique_values(as.matrix(augusta_nlcd)), iterations = 1000)
#> # A tibble: 1 x 10
#> expression min mean median max `itr/sec` mem_alloc n_gc n_itr
#> <chr> <bch:> <bch:> <bch:> <bch:> <dbl> <bch:byt> <dbl> <int>
#> 1 landscape… 36.9ms 37.5ms 37.4ms 39.9ms 26.7 4.72MB 36 964
#> # … with 1 more variable: total_time <bch:tm>
bench::mark(raster::unique(as.matrix(augusta_nlcd)), iterations = 1000)
#> # A tibble: 1 x 10
#> expression min mean median max `itr/sec` mem_alloc n_gc n_itr
#> <chr> <bch:> <bch:> <bch:> <bch:> <dbl> <bch:byt> <dbl> <int>
#> 1 raster::u… 2.92ms 3.02ms 3ms 4.04ms 331. 5.79MB 237 763
#> # … with 1 more variable: total_time <bch:tm>Created on 2019-04-24 by the reprex package (v0.2.1)
mhesselbarth commented
I will close this for now. Please re-open if needed.