matrixStats.benchmarks
t_tx_OP_y() benchmarks
This report benchmark the performance of t_tx_OP_y() against alternative methods.
Alternative methods
- t_tx_OP_y_R()
as below
> t_tx_OP_y_R <- function(x, y, OP, na.rm = FALSE) {
+ x <- t(x)
+ if (na.rm) {
+ xnok <- is.na(x)
+ ynok <- is.na(y)
+ anok <- xnok & ynok
+ unit <- switch(OP, `+` = 0, `-` = NA_real_, `*` = 1, `/` = NA_real_, stop("Unknown 'OP' operator: ",
+ OP))
+ x[xnok] <- unit
+ y[ynok] <- unit
+ }
+ ans <- switch(OP, `+` = x + y, `-` = x - y, `*` = x * y, `/` = x/y, stop("Unknown 'OP' operator: ",
+ OP))
+ if (na.rm) {
+ ans[anok] <- NA_real_
+ }
+ t(ans)
+ }
Data type “integer”
Data
> rmatrix <- function(nrow, ncol, mode = c("logical", "double", "integer", "index"), range = c(-100,
+ +100), na_prob = 0) {
+ mode <- match.arg(mode)
+ n <- nrow * ncol
+ if (mode == "logical") {
+ x <- sample(c(FALSE, TRUE), size = n, replace = TRUE)
+ } else if (mode == "index") {
+ x <- seq_len(n)
+ mode <- "integer"
+ } else {
+ x <- runif(n, min = range[1], max = range[2])
+ }
+ storage.mode(x) <- mode
+ if (na_prob > 0)
+ x[sample(n, size = na_prob * n)] <- NA
+ dim(x) <- c(nrow, ncol)
+ x
+ }
> rmatrices <- function(scale = 10, seed = 1, ...) {
+ set.seed(seed)
+ data <- list()
+ data[[1]] <- rmatrix(nrow = scale * 1, ncol = scale * 1, ...)
+ data[[2]] <- rmatrix(nrow = scale * 10, ncol = scale * 10, ...)
+ data[[3]] <- rmatrix(nrow = scale * 100, ncol = scale * 1, ...)
+ data[[4]] <- t(data[[3]])
+ data[[5]] <- rmatrix(nrow = scale * 10, ncol = scale * 100, ...)
+ data[[6]] <- t(data[[5]])
+ names(data) <- sapply(data, FUN = function(x) paste(dim(x), collapse = "x"))
+ data
+ }
> data <- rmatrices(mode = mode)
Results
10x10 vector
All elements
> x <- data[["10x10"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359480 286.3 7916910 422.9 7916910 422.9
Vcells 10761999 82.2 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x10+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.004792 | 0.0051140 | 0.0054643 | 0.0052340 | 0.0054775 | 0.01856 |
| 2 | t_tx_OP_y_R | 0.007577 | 0.0083995 | 0.1354860 | 0.0086735 | 0.0089250 | 12.63440 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.00000 | 1.000000 | 1.000000 | 1.0000 |
| 2 | t_tx_OP_y_R | 1.581177 | 1.642452 | 24.79498 | 1.657146 | 1.629393 | 680.7329 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x10+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357091 286.1 7916910 422.9 7916910 422.9
Vcells 10453134 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x10+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.005238 | 0.0056280 | 0.0061111 | 0.0059095 | 0.0061535 | 0.022069 |
| 2 | t_tx_OP_y_R | 0.008658 | 0.0093775 | 0.0100597 | 0.0097130 | 0.0099820 | 0.043773 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.652921 | 1.666222 | 1.646131 | 1.643625 | 1.622166 | 1.983461 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x10+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357154 286.2 7916910 422.9 7916910 422.9
Vcells 10453688 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x10+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.005433 | 0.0057350 | 0.0062027 | 0.0059305 | 0.006092 | 0.026583 |
| 2 | t_tx_OP_y_R | 0.008626 | 0.0096415 | 0.0102577 | 0.0099605 | 0.010307 | 0.039747 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.587705 | 1.681168 | 1.653738 | 1.679538 | 1.691891 | 1.495204 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x10+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357217 286.2 7916910 422.9 7916910 422.9
Vcells 10453730 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x10+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.005268 | 0.0054985 | 0.0059865 | 0.0056980 | 0.0058640 | 0.023809 |
| 2 | t_tx_OP_y_R | 0.008787 | 0.0091925 | 0.0101256 | 0.0094775 | 0.0098445 | 0.056867 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.00000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.667995 | 1.67182 | 1.691408 | 1.663303 | 1.678803 | 2.388466 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x10+div data. Outliers are displayed as crosses. Times are in milliseconds.
100x100 vector
All elements
> x <- data[["100x100"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357280 286.2 7916910 422.9 7916910 422.9
Vcells 10453814 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x100+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.06765 | 0.074104 | 0.0854342 | 0.0795530 | 0.083400 | 0.167465 |
| 1 | t_tx_OP_y | 0.12826 | 0.139470 | 0.1523180 | 0.1506835 | 0.153984 | 0.276345 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.00000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.895935 | 1.882085 | 1.78287 | 1.894127 | 1.846331 | 1.650166 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x100+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357343 286.2 7916910 422.9 7916910 422.9
Vcells 10454064 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x100+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.063773 | 0.071118 | 0.0766773 | 0.077736 | 0.0795685 | 0.132571 |
| 1 | t_tx_OP_y | 0.124079 | 0.139019 | 0.1490000 | 0.150793 | 0.1544910 | 0.205799 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 |
| 1 | t_tx_OP_y | 1.945635 | 1.954765 | 1.943209 | 1.939809 | 1.94161 | 1.552368 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x100+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357406 286.2 7916910 422.9 7916910 422.9
Vcells 10454360 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x100+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.076390 | 0.0802205 | 0.0881573 | 0.0865500 | 0.0935110 | 0.135884 |
| 1 | t_tx_OP_y | 0.119564 | 0.1269280 | 0.1353920 | 0.1361675 | 0.1454525 | 0.164303 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.0000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.565179 | 1.582239 | 1.5358 | 1.573281 | 1.555459 | 1.209142 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x100+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357469 286.2 7916910 422.9 7916910 422.9
Vcells 10454402 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x100+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.061477 | 0.0648335 | 0.0695980 | 0.0680330 | 0.0735405 | 0.116895 |
| 1 | t_tx_OP_y | 0.108692 | 0.1169385 | 0.1243425 | 0.1222795 | 0.1314875 | 0.147169 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 |
| 1 | t_tx_OP_y | 1.768011 | 1.803674 | 1.786581 | 1.797356 | 1.78796 | 1.258985 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x100+div data. Outliers are displayed as crosses. Times are in milliseconds.
1000x10 vector
All elements
> x <- data[["1000x10"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357532 286.2 7916910 422.9 7916910 422.9
Vcells 10455229 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x10+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.061979 | 0.0649495 | 0.0723678 | 0.0708370 | 0.0769835 | 0.137807 |
| 1 | t_tx_OP_y | 0.119178 | 0.1262600 | 0.1368965 | 0.1355065 | 0.1491560 | 0.167211 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.922877 | 1.943972 | 1.891677 | 1.912934 | 1.937506 | 1.213371 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x10+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357595 286.2 7916910 422.9 7916910 422.9
Vcells 10455637 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x10+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.063738 | 0.069978 | 0.0769204 | 0.0759065 | 0.081626 | 0.138153 |
| 1 | t_tx_OP_y | 0.119379 | 0.124481 | 0.1366055 | 0.1379715 | 0.149750 | 0.165708 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.872964 | 1.778859 | 1.775934 | 1.817651 | 1.834587 | 1.199453 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x10+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357658 286.2 7916910 422.9 7916910 422.9
Vcells 10455679 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x10+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.076391 | 0.0823275 | 0.0995711 | 0.0960780 | 0.100821 | 0.164063 |
| 1 | t_tx_OP_y | 0.118877 | 0.1275075 | 0.1473376 | 0.1447075 | 0.153880 | 0.230046 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.556165 | 1.548784 | 1.479723 | 1.506146 | 1.526269 | 1.402181 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x10+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357721 286.2 7916910 422.9 7916910 422.9
Vcells 10455721 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x10+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.059949 | 0.0641515 | 0.0692316 | 0.0676975 | 0.0735645 | 0.118778 |
| 1 | t_tx_OP_y | 0.107295 | 0.1198800 | 0.1238901 | 0.1249830 | 0.1306315 | 0.146916 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.789771 | 1.868701 | 1.789503 | 1.846198 | 1.775741 | 1.236896 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x10+div data. Outliers are displayed as crosses. Times are in milliseconds.
10x1000 vector
All elements
> x <- data[["10x1000"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357784 286.2 7916910 422.9 7916910 422.9
Vcells 10455743 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x1000+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.061975 | 0.0647750 | 0.0712675 | 0.069769 | 0.0767525 | 0.107036 |
| 1 | t_tx_OP_y | 0.120295 | 0.1253595 | 0.1375982 | 0.134508 | 0.1506860 | 0.211431 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.941025 | 1.935307 | 1.930729 | 1.927905 | 1.963272 | 1.975326 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x1000+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357847 286.2 7916910 422.9 7916910 422.9
Vcells 10455785 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x1000+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.072982 | 0.0771935 | 0.0821623 | 0.0794455 | 0.0848795 | 0.131850 |
| 1 | t_tx_OP_y | 0.124240 | 0.1338980 | 0.1440777 | 0.1481265 | 0.1509870 | 0.182203 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.702338 | 1.734576 | 1.753574 | 1.864505 | 1.778839 | 1.381896 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x1000+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357910 286.2 7916910 422.9 7916910 422.9
Vcells 10456366 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x1000+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.076394 | 0.082199 | 0.0891491 | 0.0888070 | 0.096378 | 0.127886 |
| 1 | t_tx_OP_y | 0.120029 | 0.125068 | 0.1373506 | 0.1347325 | 0.150713 | 0.178859 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 |
| 1 | t_tx_OP_y | 1.571184 | 1.521527 | 1.540684 | 1.517138 | 1.56377 | 1.398581 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x1000+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5357973 286.2 7916910 422.9 7916910 422.9
Vcells 10456408 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x1000+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.063549 | 0.0700900 | 0.0772890 | 0.0731640 | 0.0757885 | 0.13497 |
| 1 | t_tx_OP_y | 0.114001 | 0.1267145 | 0.1355822 | 0.1326015 | 0.1368990 | 0.22090 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 |
| 1 | t_tx_OP_y | 1.793907 | 1.807883 | 1.754225 | 1.812387 | 1.806329 | 1.63666 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+10x1000+div data. Outliers are displayed as crosses. Times are in milliseconds.
100x1000 vector
All elements
> x <- data[["100x1000"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358036 286.2 7916910 422.9 7916910 422.9
Vcells 10456492 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x1000+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.443026 | 0.5529485 | 0.7070996 | 0.7927105 | 0.802601 | 1.467060 |
| 1 | t_tx_OP_y | 0.895442 | 1.0111895 | 1.0821621 | 1.0394900 | 1.133057 | 1.492148 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 2.021195 | 1.828723 | 1.530424 | 1.311311 | 1.411731 | 1.017101 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x1000+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358099 286.2 7916910 422.9 7916910 422.9
Vcells 10457177 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x1000+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.437097 | 0.4859820 | 0.6621817 | 0.744716 | 0.794876 | 0.983471 |
| 1 | t_tx_OP_y | 0.895992 | 0.9679345 | 1.0380734 | 1.015048 | 1.057953 | 1.490787 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.00000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 2.04987 | 1.991709 | 1.567656 | 1.362999 | 1.330966 | 1.515842 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x1000+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358162 286.2 7916910 422.9 7916910 422.9
Vcells 10457219 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x1000+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.545843 | 0.5728210 | 0.7725055 | 0.862313 | 0.910431 | 1.019358 |
| 1 | t_tx_OP_y | 0.895545 | 0.9563165 | 1.0121836 | 1.013592 | 1.025589 | 1.389407 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.640664 | 1.669486 | 1.310261 | 1.175434 | 1.126488 | 1.363022 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x1000+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358225 286.2 7916910 422.9 7916910 422.9
Vcells 10457261 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x1000+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.483148 | 0.6532375 | 4.822539 | 0.866531 | 0.982403 | 401.82914 |
| 1 | t_tx_OP_y | 0.955124 | 1.0097195 | 1.094749 | 1.041548 | 1.144797 | 1.60297 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.0000000 | 1.000000 | 1.000000 | 1.0000000 |
| 1 | t_tx_OP_y | 1.976877 | 1.545716 | 0.2270068 | 1.201974 | 1.165303 | 0.0039892 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+100x1000+div data. Outliers are displayed as crosses. Times are in milliseconds.
1000x100 vector
All elements
> x <- data[["1000x100"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358288 286.2 7916910 422.9 7916910 422.9
Vcells 10457753 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x100+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.436198 | 0.4904155 | 0.6640799 | 0.704767 | 0.8130565 | 0.903118 |
| 1 | t_tx_OP_y | 0.889954 | 0.9941670 | 1.0387363 | 1.010934 | 1.0500310 | 1.481849 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 2.040252 | 2.027193 | 1.564174 | 1.434423 | 1.291461 | 1.640814 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x100+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358351 286.2 7916910 422.9 7916910 422.9
Vcells 10458574 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x100+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.465795 | 0.5016255 | 0.6928661 | 0.7519325 | 0.8368415 | 0.967820 |
| 1 | t_tx_OP_y | 0.892380 | 0.9707000 | 1.0395785 | 1.0130905 | 1.0733240 | 1.478113 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 |
| 1 | t_tx_OP_y | 1.915821 | 1.935109 | 1.500403 | 1.347316 | 1.282589 | 1.52726 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x100+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358414 286.2 7916910 422.9 7916910 422.9
Vcells 10458616 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x100+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.542607 | 0.6073425 | 0.7908243 | 0.903643 | 0.9144905 | 1.250930 |
| 1 | t_tx_OP_y | 0.874097 | 0.9193765 | 1.0101588 | 1.005931 | 1.0205115 | 1.780452 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.610921 | 1.513769 | 1.277349 | 1.113195 | 1.115935 | 1.423303 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x100+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358477 286.2 7916910 422.9 7916910 422.9
Vcells 10458658 79.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x100+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.455946 | 0.5099905 | 0.835676 | 0.895682 | 0.9866875 | 7.273645 |
| 1 | t_tx_OP_y | 0.859561 | 0.9779945 | 1.022629 | 1.007275 | 1.0417695 | 1.377401 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.0000000 |
| 1 | t_tx_OP_y | 1.885225 | 1.917672 | 1.223714 | 1.124591 | 1.055825 | 0.1893687 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on integer+1000x100+div data. Outliers are displayed as crosses. Times are in milliseconds.
Data type “double”
Data
> rmatrix <- function(nrow, ncol, mode = c("logical", "double", "integer", "index"), range = c(-100,
+ +100), na_prob = 0) {
+ mode <- match.arg(mode)
+ n <- nrow * ncol
+ if (mode == "logical") {
+ x <- sample(c(FALSE, TRUE), size = n, replace = TRUE)
+ } else if (mode == "index") {
+ x <- seq_len(n)
+ mode <- "integer"
+ } else {
+ x <- runif(n, min = range[1], max = range[2])
+ }
+ storage.mode(x) <- mode
+ if (na_prob > 0)
+ x[sample(n, size = na_prob * n)] <- NA
+ dim(x) <- c(nrow, ncol)
+ x
+ }
> rmatrices <- function(scale = 10, seed = 1, ...) {
+ set.seed(seed)
+ data <- list()
+ data[[1]] <- rmatrix(nrow = scale * 1, ncol = scale * 1, ...)
+ data[[2]] <- rmatrix(nrow = scale * 10, ncol = scale * 10, ...)
+ data[[3]] <- rmatrix(nrow = scale * 100, ncol = scale * 1, ...)
+ data[[4]] <- t(data[[3]])
+ data[[5]] <- rmatrix(nrow = scale * 10, ncol = scale * 100, ...)
+ data[[6]] <- t(data[[5]])
+ names(data) <- sapply(data, FUN = function(x) paste(dim(x), collapse = "x"))
+ data
+ }
> data <- rmatrices(mode = mode)
Results
10x10 vector
All elements
> x <- data[["10x10"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358540 286.2 7916910 422.9 7916910 422.9
Vcells 10573266 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x10+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.005035 | 0.0053740 | 0.0057734 | 0.0055370 | 0.0057795 | 0.021347 |
| 2 | t_tx_OP_y_R | 0.008818 | 0.0092995 | 0.0100136 | 0.0095395 | 0.0098020 | 0.047716 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.751341 | 1.730462 | 1.734433 | 1.722864 | 1.695995 | 2.235256 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x10+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358603 286.2 7916910 422.9 7916910 422.9
Vcells 10574268 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x10+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.004835 | 0.005356 | 0.0057907 | 0.0055375 | 0.0058005 | 0.024568 |
| 2 | t_tx_OP_y_R | 0.008984 | 0.009386 | 0.0100435 | 0.0096180 | 0.0099385 | 0.045135 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.858118 | 1.752427 | 1.734414 | 1.736885 | 1.713387 | 1.837146 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x10+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358666 286.2 7916910 422.9 7916910 422.9
Vcells 10574310 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x10+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.005113 | 0.005387 | 0.0059391 | 0.0056490 | 0.005853 | 0.031680 |
| 2 | t_tx_OP_y_R | 0.008733 | 0.009420 | 0.0100366 | 0.0096425 | 0.009924 | 0.042358 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.707999 | 1.748654 | 1.689915 | 1.706939 | 1.695541 | 1.337058 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x10+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358729 286.2 7916910 422.9 7916910 422.9
Vcells 10574352 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x10+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.005270 | 0.0055515 | 0.0059585 | 0.0057480 | 0.0059570 | 0.023098 |
| 2 | t_tx_OP_y_R | 0.009214 | 0.0098395 | 0.0105604 | 0.0101205 | 0.0104115 | 0.046769 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.748387 | 1.772404 | 1.772329 | 1.760699 | 1.747776 | 2.024807 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x10+div data. Outliers are displayed as crosses. Times are in milliseconds.
100x100 vector
All elements
> x <- data[["100x100"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358792 286.2 7916910 422.9 7916910 422.9
Vcells 10574478 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x100+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.059767 | 0.063104 | 0.0694316 | 0.069792 | 0.0719580 | 0.111210 |
| 1 | t_tx_OP_y | 0.103714 | 0.108578 | 0.1184819 | 0.119837 | 0.1221485 | 0.168989 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.00000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.735305 | 1.72062 | 1.706454 | 1.717059 | 1.697497 | 1.519549 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x100+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358855 286.2 7916910 422.9 7916910 422.9
Vcells 10574520 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x100+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.059237 | 0.0638345 | 0.0690666 | 0.0691460 | 0.072659 | 0.101505 |
| 1 | t_tx_OP_y | 0.099537 | 0.1073610 | 0.1149339 | 0.1160625 | 0.121194 | 0.146602 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.680318 | 1.681865 | 1.664104 | 1.678514 | 1.667983 | 1.444284 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x100+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358918 286.2 7916910 422.9 7916910 422.9
Vcells 10575688 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x100+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.055158 | 0.0579820 | 0.0633623 | 0.061923 | 0.0652885 | 0.121917 |
| 1 | t_tx_OP_y | 0.096552 | 0.0996905 | 0.1068064 | 0.104457 | 0.1126995 | 0.133660 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 |
| 1 | t_tx_OP_y | 1.750462 | 1.719335 | 1.685647 | 1.686885 | 1.726177 | 1.09632 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x100+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5358981 286.3 7916910 422.9 7916910 422.9
Vcells 10575730 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x100+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.061108 | 0.065382 | 0.0895766 | 0.0763640 | 0.114400 | 0.153698 |
| 1 | t_tx_OP_y | 0.096898 | 0.104231 | 0.1284784 | 0.1179155 | 0.156531 | 0.181925 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.585684 | 1.594185 | 1.434285 | 1.544124 | 1.368278 | 1.183652 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x100+div data. Outliers are displayed as crosses. Times are in milliseconds.
1000x10 vector
All elements
> x <- data[["1000x10"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359044 286.3 7916910 422.9 7916910 422.9
Vcells 10576672 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x10+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.058142 | 0.0615020 | 0.0672183 | 0.0679220 | 0.0709270 | 0.112063 |
| 1 | t_tx_OP_y | 0.099063 | 0.1069205 | 0.1136465 | 0.1119715 | 0.1207585 | 0.137365 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.703811 | 1.738488 | 1.690708 | 1.648531 | 1.702575 | 1.225784 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x10+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359107 286.3 7916910 422.9 7916910 422.9
Vcells 10576714 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x10+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.061490 | 0.066353 | 0.0718577 | 0.0721585 | 0.0746045 | 0.116601 |
| 1 | t_tx_OP_y | 0.102235 | 0.106723 | 0.1144989 | 0.1152975 | 0.1206185 | 0.136569 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.662628 | 1.608413 | 1.593412 | 1.597837 | 1.616772 | 1.171251 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x10+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359170 286.3 7916910 422.9 7916910 422.9
Vcells 10576756 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x10+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.059454 | 0.0630695 | 0.0683460 | 0.0662105 | 0.07064 | 0.110499 |
| 1 | t_tx_OP_y | 0.102572 | 0.1067415 | 0.1129202 | 0.1114085 | 0.11782 | 0.146247 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.725233 | 1.692443 | 1.652186 | 1.682641 | 1.667893 | 1.323514 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x10+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359233 286.3 7916910 422.9 7916910 422.9
Vcells 10576798 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x10+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.061076 | 0.0652675 | 0.0700300 | 0.0683380 | 0.0733110 | 0.125911 |
| 1 | t_tx_OP_y | 0.095999 | 0.1031375 | 0.1110227 | 0.1117705 | 0.1163545 | 0.144348 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.571796 | 1.580227 | 1.585361 | 1.635554 | 1.587136 | 1.146429 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x10+div data. Outliers are displayed as crosses. Times are in milliseconds.
10x1000 vector
All elements
> x <- data[["10x1000"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359296 286.3 7916910 422.9 7916910 422.9
Vcells 10575856 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x1000+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.060446 | 0.0635905 | 0.0687139 | 0.0682480 | 0.0717065 | 0.099246 |
| 1 | t_tx_OP_y | 0.100012 | 0.1046020 | 0.1121239 | 0.1124885 | 0.1178660 | 0.141207 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.654568 | 1.644931 | 1.631751 | 1.648232 | 1.643728 | 1.422798 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x1000+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359359 286.3 7916910 422.9 7916910 422.9
Vcells 10577276 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x1000+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.059049 | 0.0632165 | 0.0691208 | 0.0675185 | 0.073197 | 0.114610 |
| 1 | t_tx_OP_y | 0.096025 | 0.1031365 | 0.1092506 | 0.1079440 | 0.115923 | 0.132524 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.626192 | 1.631481 | 1.580576 | 1.598732 | 1.583712 | 1.156304 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x1000+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359422 286.3 7916910 422.9 7916910 422.9
Vcells 10577318 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x1000+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.058980 | 0.063851 | 0.0685217 | 0.0683940 | 0.0716965 | 0.099835 |
| 1 | t_tx_OP_y | 0.097612 | 0.105664 | 0.1129154 | 0.1137595 | 0.1192080 | 0.142361 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.655002 | 1.654853 | 1.647878 | 1.663296 | 1.662675 | 1.425963 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x1000+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359485 286.3 7916910 422.9 7916910 422.9
Vcells 10577360 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x1000+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.060063 | 0.0649055 | 0.0696192 | 0.0704220 | 0.0732225 | 0.102117 |
| 1 | t_tx_OP_y | 0.095896 | 0.0988145 | 0.1077506 | 0.1075465 | 0.1167190 | 0.141481 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.00000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.59659 | 1.522436 | 1.547714 | 1.527172 | 1.594032 | 1.385479 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+10x1000+div data. Outliers are displayed as crosses. Times are in milliseconds.
100x1000 vector
All elements
> x <- data[["100x1000"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359548 286.3 7916910 422.9 7916910 422.9
Vcells 10577486 80.7 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x1000+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.901792 | 0.9497850 | 1.041943 | 1.014856 | 1.131563 | 1.276441 |
| 2 | t_tx_OP_y_R | 0.484047 | 0.5728035 | 1.073689 | 1.091916 | 1.212484 | 14.009955 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.0000000 | 1.0000000 | 1.000000 | 1.000000 | 1.000000 | 1.0000 |
| 2 | t_tx_OP_y_R | 0.5367612 | 0.6030875 | 1.030468 | 1.075932 | 1.071514 | 10.9758 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x1000+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359611 286.3 7916910 422.9 7916910 422.9
Vcells 10577528 80.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x1000+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.795778 | 0.9272400 | 1.1092133 | 0.9519695 | 1.004517 | 14.771763 |
| 2 | t_tx_OP_y_R | 0.473895 | 0.5243275 | 0.8600482 | 1.0775025 | 1.113700 | 1.339528 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.0000000 | 1.0000000 | 1.0000000 | 1.000000 | 1.000000 | 1.0000000 |
| 2 | t_tx_OP_y_R | 0.5955116 | 0.5654712 | 0.7753678 | 1.131867 | 1.108692 | 0.0906817 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x1000+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359674 286.3 7916910 422.9 7916910 422.9
Vcells 10577570 80.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x1000+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.419482 | 0.5275785 | 0.9564862 | 0.883330 | 1.189644 | 6.896142 |
| 1 | t_tx_OP_y | 0.776520 | 0.9042240 | 0.9880226 | 0.955963 | 1.063478 | 1.504890 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.00000 | 1.000000 | 1.000000 | 1.000000 | 1.0000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.85114 | 1.713914 | 1.032971 | 1.082226 | 0.8939456 | 0.218222 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x1000+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359737 286.3 7916910 422.9 7916910 422.9
Vcells 10577612 80.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x1000+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.437299 | 0.5197425 | 0.8910695 | 0.6303440 | 1.163025 | 7.809049 |
| 1 | t_tx_OP_y | 0.760480 | 0.8857180 | 0.9497605 | 0.9507415 | 1.019939 | 1.138997 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.0000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.739039 | 1.704148 | 1.065866 | 1.50829 | 0.8769713 | 0.145856 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+100x1000+div data. Outliers are displayed as crosses. Times are in milliseconds.
1000x100 vector
All elements
> x <- data[["1000x100"]]
> y <- x[, 1L]
> OP
[1] "+"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359800 286.3 7916910 422.9 7916910 422.9
Vcells 10580175 80.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x100+add data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.866190 | 0.927667 | 1.004176 | 0.979614 | 1.071657 | 1.274754 |
| 2 | t_tx_OP_y_R | 0.461338 | 0.508870 | 1.032630 | 1.088598 | 1.201562 | 14.663678 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.0000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 |
| 2 | t_tx_OP_y_R | 0.532606 | 0.5485481 | 1.028336 | 1.111252 | 1.121218 | 11.50314 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x100+add data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "-"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359863 286.3 7916910 422.9 7916910 422.9
Vcells 10580217 80.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x100+sub data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.425795 | 0.497865 | 0.8521543 | 0.6009190 | 1.1347170 | 7.188615 |
| 1 | t_tx_OP_y | 0.767195 | 0.891814 | 0.9380264 | 0.9376575 | 0.9555995 | 1.440594 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.0000000 | 1.0000000 |
| 1 | t_tx_OP_y | 1.801794 | 1.791277 | 1.100771 | 1.560372 | 0.8421479 | 0.2003994 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x100+sub data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "*"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359926 286.3 7916910 422.9 7916910 422.9
Vcells 10580259 80.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x100+mul data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.814675 | 0.9195295 | 0.9680476 | 0.9577365 | 1.021850 | 1.191257 |
| 2 | t_tx_OP_y_R | 0.467949 | 0.5359960 | 1.0360612 | 1.1002600 | 1.189913 | 14.779634 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.0000000 | 1.0000000 | 1.000000 | 1.000000 | 1.00000 | 1.00000 |
| 2 | t_tx_OP_y_R | 0.5743996 | 0.5829025 | 1.070259 | 1.148813 | 1.16447 | 12.40676 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x100+mul data. Outliers are displayed as crosses. Times are in milliseconds.
> OP
[1] "/"
> stats <- microbenchmark(t_tx_OP_y = t_tx_OP_y(x, y, OP = OP, na.rm = FALSE), t_tx_OP_y_R = t_tx_OP_y_R(x,
+ y, OP = OP, na.rm = FALSE), unit = "ms")
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5359989 286.3 7916910 422.9 7916910 422.9
Vcells 10580301 80.8 39038428 297.9 94934136 724.3
Table: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x100+div data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.830898 | 0.9044995 | 0.9589714 | 0.920863 | 1.021394 | 1.207078 |
| 2 | t_tx_OP_y_R | 0.482380 | 0.5420260 | 1.0161272 | 1.052486 | 1.147881 | 14.691195 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.0000000 | 1.0000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 |
| 2 | t_tx_OP_y_R | 0.5805526 | 0.5992552 | 1.059601 | 1.142934 | 1.123838 | 12.17087 |
Figure: Benchmarking of t_tx_OP_y() and t_tx_OP_y_R() on double+1000x100+div data. Outliers are displayed as crosses. Times are in milliseconds.
Appendix
Session information
R version 4.1.1 Patched (2021-08-10 r80727)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.5 LTS
Matrix products: default
BLAS: /home/hb/software/R-devel/R-4-1-branch/lib/R/lib/libRblas.so
LAPACK: /home/hb/software/R-devel/R-4-1-branch/lib/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] microbenchmark_1.4-7 matrixStats_0.60.0 ggplot2_3.3.5
[4] knitr_1.33 R.devices_2.17.0 R.utils_2.10.1
[7] R.oo_1.24.0 R.methodsS3_1.8.1-9001 history_0.0.1-9000
loaded via a namespace (and not attached):
[1] Biobase_2.52.0 httr_1.4.2 splines_4.1.1
[4] bit64_4.0.5 network_1.17.1 assertthat_0.2.1
[7] highr_0.9 stats4_4.1.1 blob_1.2.2
[10] GenomeInfoDbData_1.2.6 robustbase_0.93-8 pillar_1.6.2
[13] RSQLite_2.2.8 lattice_0.20-44 glue_1.4.2
[16] digest_0.6.27 XVector_0.32.0 colorspace_2.0-2
[19] Matrix_1.3-4 XML_3.99-0.7 pkgconfig_2.0.3
[22] zlibbioc_1.38.0 genefilter_1.74.0 purrr_0.3.4
[25] ergm_4.1.2 xtable_1.8-4 scales_1.1.1
[28] tibble_3.1.4 annotate_1.70.0 KEGGREST_1.32.0
[31] farver_2.1.0 generics_0.1.0 IRanges_2.26.0
[34] ellipsis_0.3.2 cachem_1.0.6 withr_2.4.2
[37] BiocGenerics_0.38.0 mime_0.11 survival_3.2-13
[40] magrittr_2.0.1 crayon_1.4.1 statnet.common_4.5.0
[43] memoise_2.0.0 laeken_0.5.1 fansi_0.5.0
[46] R.cache_0.15.0 MASS_7.3-54 R.rsp_0.44.0
[49] progressr_0.8.0 tools_4.1.1 lifecycle_1.0.0
[52] S4Vectors_0.30.0 trust_0.1-8 munsell_0.5.0
[55] tabby_0.0.1-9001 AnnotationDbi_1.54.1 Biostrings_2.60.2
[58] compiler_4.1.1 GenomeInfoDb_1.28.1 rlang_0.4.11
[61] grid_4.1.1 RCurl_1.98-1.4 cwhmisc_6.6
[64] rstudioapi_0.13 rappdirs_0.3.3 startup_0.15.0-9000
[67] labeling_0.4.2 bitops_1.0-7 base64enc_0.1-3
[70] boot_1.3-28 gtable_0.3.0 DBI_1.1.1
[73] markdown_1.1 R6_2.5.1 lpSolveAPI_5.5.2.0-17.7
[76] rle_0.9.2 dplyr_1.0.7 fastmap_1.1.0
[79] bit_4.0.4 utf8_1.2.2 parallel_4.1.1
[82] Rcpp_1.0.7 vctrs_0.3.8 png_0.1-7
[85] DEoptimR_1.0-9 tidyselect_1.1.1 xfun_0.25
[88] coda_0.19-4
Total processing time was 1.24 mins.
Reproducibility
To reproduce this report, do:
html <- matrixStats:::benchmark('t_tx_OP_y')
Copyright Henrik Bengtsson. Last updated on 2021-08-25 22:51:37 (+0200 UTC). Powered by RSP.