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 5347427 285.6 8529671 455.6 8529671 455.6
Vcells 10709330 81.8 39910282 304.5 101881463 777.3
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 | 0.004983 | 0.005279 | 0.0056798 | 0.005475 | 0.0056840 | 0.01901 |
| 2 | t_tx_OP_y_R | 0.007547 | 0.008338 | 0.1349789 | 0.008664 | 0.0090305 | 12.59405 |
| 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 | 1.514549 | 1.579466 | 23.76457 | 1.582466 | 1.588758 | 662.4961 |
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 5345038 285.5 8529671 455.6 8529671 455.6
Vcells 10400465 79.4 39910282 304.5 101881463 777.3
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 | 0.005664 | 0.0060235 | 0.0064878 | 0.006254 | 0.0065040 | 0.023962 |
| 2 | t_tx_OP_y_R | 0.008637 | 0.0094145 | 0.0103448 | 0.009834 | 0.0102425 | 0.046976 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.0000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.524894 | 1.562962 | 1.594488 | 1.572434 | 1.5748 | 1.960437 |
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 5345101 285.5 8529671 455.6 8529671 455.6
Vcells 10401019 79.4 39910282 304.5 101881463 777.3
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 | 0.005545 | 0.0058525 | 0.0063719 | 0.006114 | 0.006258 | 0.028545 |
| 2 | t_tx_OP_y_R | 0.008728 | 0.0096525 | 0.0103266 | 0.010018 | 0.010333 | 0.038994 |
| 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 | 1.574031 | 1.649295 | 1.620653 | 1.638535 | 1.651166 | 1.366054 |
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 5345164 285.5 8529671 455.6 8529671 455.6
Vcells 10401061 79.4 39910282 304.5 101881463 777.3
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 | 0.005692 | 0.005940 | 0.0065432 | 0.0061915 | 0.0064425 | 0.023614 |
| 2 | t_tx_OP_y_R | 0.008903 | 0.009336 | 0.0104996 | 0.0097680 | 0.0102045 | 0.044990 |
| 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 | 1.564125 | 1.571717 | 1.604658 | 1.577647 | 1.583935 | 1.905226 |
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 5345227 285.5 8529671 455.6 8529671 455.6
Vcells 10401145 79.4 39910282 304.5 101881463 777.3
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 | 0.061055 | 0.0634935 | 0.0695768 | 0.0674600 | 0.073376 | 0.109567 |
| 1 | t_tx_OP_y | 0.131513 | 0.1367450 | 0.1499521 | 0.1466425 | 0.158129 | 0.196721 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 | 1.00000 |
| 1 | t_tx_OP_y | 2.154009 | 2.153685 | 2.155204 | 2.17377 | 2.155051 | 1.79544 |
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 5345290 285.5 8529671 455.6 8529671 455.6
Vcells 10401394 79.4 39910282 304.5 101881463 777.3
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 | 0.060371 | 0.0628145 | 0.0693277 | 0.0677580 | 0.0738335 | 0.108615 |
| 1 | t_tx_OP_y | 0.131984 | 0.1376405 | 0.1514367 | 0.1500385 | 0.1604225 | 0.202590 |
| 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 | 2.186215 | 2.191222 | 2.184359 | 2.214329 | 2.17276 | 1.865212 |
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 5345353 285.5 8529671 455.6 8529671 455.6
Vcells 10401691 79.4 39910282 304.5 101881463 777.3
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 | 0.074205 | 0.078724 | 0.0858203 | 0.0835490 | 0.0900225 | 0.136397 |
| 1 | t_tx_OP_y | 0.123745 | 0.128419 | 0.1416537 | 0.1399055 | 0.1514950 | 0.176588 |
| 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 | 1.66761 | 1.631256 | 1.650585 | 1.674532 | 1.682857 | 1.294662 |
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 5345416 285.5 8529671 455.6 8529671 455.6
Vcells 10401733 79.4 39910282 304.5 101881463 777.3
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 | 0.058448 | 0.0603865 | 0.0661994 | 0.0637955 | 0.070090 | 0.123605 |
| 1 | t_tx_OP_y | 0.124958 | 0.1303255 | 0.1421488 | 0.1396770 | 0.151172 | 0.180366 |
| 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 | 2.137935 | 2.158189 | 2.147283 | 2.189449 | 2.156827 | 1.459213 |
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 5345479 285.5 8529671 455.6 8529671 455.6
Vcells 10402562 79.4 39910282 304.5 101881463 777.3
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 | 0.062701 | 0.0642275 | 0.0715736 | 0.0694975 | 0.076245 | 0.129545 |
| 1 | t_tx_OP_y | 0.135152 | 0.1394690 | 0.1505490 | 0.1495850 | 0.162141 | 0.186400 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.0000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 2.1555 | 2.171484 | 2.103417 | 2.15238 | 2.126579 | 1.438882 |
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 5345542 285.5 8529671 455.6 8529671 455.6
Vcells 10402968 79.4 39910282 304.5 101881463 777.3
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 | 0.065232 | 0.0701835 | 0.0768766 | 0.0754960 | 0.0824515 | 0.136001 |
| 1 | t_tx_OP_y | 0.135227 | 0.1403765 | 0.1520034 | 0.1508315 | 0.1618130 | 0.193719 |
| 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 | 2.073016 | 2.000135 | 1.977237 | 1.997874 | 1.962523 | 1.424394 |
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 5345605 285.5 8529671 455.6 8529671 455.6
Vcells 10403010 79.4 39910282 304.5 101881463 777.3
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 | 0.074346 | 0.0781305 | 0.0871916 | 0.085119 | 0.0933965 | 0.129177 |
| 1 | t_tx_OP_y | 0.126527 | 0.1272910 | 0.1399157 | 0.138084 | 0.1467150 | 0.187362 |
| 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 | 1.701867 | 1.62921 | 1.604692 | 1.622246 | 1.570883 | 1.450428 |
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 5345668 285.5 8529671 455.6 8529671 455.6
Vcells 10403052 79.4 39910282 304.5 101881463 777.3
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 | 0.057455 | 0.0603140 | 0.0663456 | 0.064329 | 0.0699235 | 0.117929 |
| 1 | t_tx_OP_y | 0.128089 | 0.1330535 | 0.1434063 | 0.142823 | 0.1537220 | 0.175953 |
| 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 | 2.229379 | 2.206014 | 2.161505 | 2.220196 | 2.198431 | 1.492025 |
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 5345731 285.5 8529671 455.6 8529671 455.6
Vcells 10403076 79.4 39910282 304.5 101881463 777.3
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 | 0.060642 | 0.0648365 | 0.0705814 | 0.0681025 | 0.0756035 | 0.107864 |
| 1 | t_tx_OP_y | 0.134803 | 0.1415020 | 0.1550631 | 0.1545525 | 0.1669140 | 0.201749 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 2.222931 | 2.182444 | 2.196939 | 2.26941 | 2.207755 | 1.870402 |
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 5345794 285.5 8529671 455.6 8529671 455.6
Vcells 10403118 79.4 39910282 304.5 101881463 777.3
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 | 0.060060 | 0.0626605 | 0.0679827 | 0.0649995 | 0.0725225 | 0.113947 |
| 1 | t_tx_OP_y | 0.134188 | 0.1394350 | 0.1524524 | 0.1494770 | 0.1608630 | 0.196263 |
| 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 | 2.234232 | 2.225246 | 2.242519 | 2.299664 | 2.218112 | 1.722406 |
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 5345857 285.5 8529671 455.6 8529671 455.6
Vcells 10403699 79.4 39910282 304.5 101881463 777.3
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 | 0.074524 | 0.0785795 | 0.0869808 | 0.0837915 | 0.096217 | 0.124918 |
| 1 | t_tx_OP_y | 0.125315 | 0.1302115 | 0.1429299 | 0.1394780 | 0.151504 | 0.183558 |
| 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 | 1.681539 | 1.657067 | 1.643234 | 1.664584 | 1.574607 | 1.469428 |
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 5345920 285.6 8529671 455.6 8529671 455.6
Vcells 10403741 79.4 39910282 304.5 101881463 777.3
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 | 0.055967 | 0.0604850 | 0.0657797 | 0.0644070 | 0.070647 | 0.101531 |
| 1 | t_tx_OP_y | 0.128301 | 0.1338435 | 0.1446149 | 0.1431405 | 0.153900 | 0.187839 |
| 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 | 2.29244 | 2.212838 | 2.198473 | 2.222437 | 2.178437 | 1.850065 |
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 5345983 285.6 8529671 455.6 8529671 455.6
Vcells 10403825 79.4 39910282 304.5 101881463 777.3
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 | 0.435940 | 0.497190 | 0.6985335 | 0.8027805 | 0.835507 | 1.318825 |
| 1 | t_tx_OP_y | 1.017713 | 1.045521 | 1.1695583 | 1.1657810 | 1.207005 | 1.671379 |
| 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 | 2.334525 | 2.102859 | 1.674305 | 1.452179 | 1.444638 | 1.267324 |
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 5346046 285.6 8529671 455.6 8529671 455.6
Vcells 10404512 79.4 39910282 304.5 101881463 777.3
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 | 0.428122 | 0.4538365 | 0.6683583 | 0.7873465 | 0.814496 | 0.893482 |
| 1 | t_tx_OP_y | 1.018072 | 1.0488740 | 1.1658298 | 1.1675695 | 1.193373 | 1.690468 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000 |
| 1 | t_tx_OP_y | 2.377995 | 2.311128 | 1.744319 | 1.482917 | 1.465167 | 1.892 |
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 5346109 285.6 8529671 455.6 8529671 455.6
Vcells 10404554 79.4 39910282 304.5 101881463 777.3
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 | 0.545050 | 0.5943725 | 0.8017725 | 0.9041235 | 0.947387 | 1.044934 |
| 1 | t_tx_OP_y | 0.953348 | 1.0081735 | 1.0901686 | 1.1026545 | 1.134078 | 1.453030 |
| 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 | 1.749102 | 1.696198 | 1.359698 | 1.219584 | 1.197058 | 1.390547 |
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 5346172 285.6 8529671 455.6 8529671 455.6
Vcells 10404596 79.4 39910282 304.5 101881463 777.3
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 | 0.435902 | 0.526530 | 0.9233374 | 0.8792105 | 0.9903645 | 14.289470 |
| 1 | t_tx_OP_y | 1.044746 | 1.195492 | 1.2115370 | 1.2020195 | 1.2269765 | 1.601834 |
| 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 | 2.396745 | 2.270511 | 1.312128 | 1.367158 | 1.238914 | 0.1120989 |
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 5346235 285.6 8529671 455.6 8529671 455.6
Vcells 10405088 79.4 39910282 304.5 101881463 777.3
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 | 0.431692 | 0.474321 | 0.6781517 | 0.804342 | 0.837447 | 0.907436 |
| 1 | t_tx_OP_y | 1.009793 | 1.082068 | 1.1671711 | 1.166275 | 1.193581 | 1.680233 |
| 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 | 2.339151 | 2.281299 | 1.721106 | 1.449974 | 1.425261 | 1.851627 |
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 5346298 285.6 8529671 455.6 8529671 455.6
Vcells 10405898 79.4 39910282 304.5 101881463 777.3
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 | 0.469884 | 0.482479 | 0.7005398 | 0.8192285 | 0.859843 | 0.933895 |
| 1 | t_tx_OP_y | 1.010496 | 1.121287 | 1.1767411 | 1.1677850 | 1.219901 | 1.729062 |
| 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 | 2.150522 | 2.324012 | 1.679763 | 1.425469 | 1.418749 | 1.851452 |
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 5346361 285.6 8529671 455.6 8529671 455.6
Vcells 10405940 79.4 39910282 304.5 101881463 777.3
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 | 0.539310 | 0.587284 | 0.7971859 | 0.9108645 | 0.9490335 | 1.014637 |
| 1 | t_tx_OP_y | 0.945263 | 0.992387 | 1.0882033 | 1.0942330 | 1.1284150 | 1.453397 |
| 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 | 1.752727 | 1.689791 | 1.365056 | 1.201313 | 1.189015 | 1.43243 |
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 5346424 285.6 8529671 455.6 8529671 455.6
Vcells 10405982 79.4 39910282 304.5 101881463 777.3
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 | 0.412670 | 0.505700 | 0.8495244 | 0.883659 | 0.9953975 | 7.427088 |
| 1 | t_tx_OP_y | 1.043154 | 1.188196 | 1.2030077 | 1.196073 | 1.2164060 | 1.544931 |
| 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 | 2.527816 | 2.349607 | 1.416096 | 1.353546 | 1.22203 | 0.208013 |
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 5346487 285.6 8529671 455.6 8529671 455.6
Vcells 10520590 80.3 39910282 304.5 101881463 777.3
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 | 0.005459 | 0.0057035 | 0.0061170 | 0.0059140 | 0.006135 | 0.022790 |
| 2 | t_tx_OP_y_R | 0.009066 | 0.0094900 | 0.0101417 | 0.0097875 | 0.010136 | 0.041912 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 |
| 2 | t_tx_OP_y_R | 1.660744 | 1.663891 | 1.657957 | 1.654971 | 1.65216 | 1.839052 |
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 5346550 285.6 8529671 455.6 8529671 455.6
Vcells 10521603 80.3 39910282 304.5 101881463 777.3
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 | 0.005451 | 0.0060930 | 0.0068629 | 0.0065165 | 0.007105 | 0.026828 |
| 2 | t_tx_OP_y_R | 0.009310 | 0.0104975 | 0.0119148 | 0.0111375 | 0.011880 | 0.053518 |
| 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 | 1.707944 | 1.722879 | 1.736114 | 1.709123 | 1.672062 | 1.994856 |
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 5346613 285.6 8529671 455.6 8529671 455.6
Vcells 10521645 80.3 39910282 304.5 101881463 777.3
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 | 0.005129 | 0.005423 | 0.0060183 | 0.0056055 | 0.0057470 | 0.043785 |
| 2 | t_tx_OP_y_R | 0.008262 | 0.008998 | 0.0096557 | 0.0092815 | 0.0094955 | 0.044500 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.00000 | 1.000000 | 1.00000 | 1.000000 | 1.000000 | 1.00000 |
| 2 | t_tx_OP_y_R | 1.61084 | 1.659229 | 1.60439 | 1.655784 | 1.652253 | 1.01633 |
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 5346676 285.6 8529671 455.6 8529671 455.6
Vcells 10521687 80.3 39910282 304.5 101881463 777.3
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 | 0.005392 | 0.0056825 | 0.0060908 | 0.0059350 | 0.0061090 | 0.021312 |
| 2 | t_tx_OP_y_R | 0.009053 | 0.0095185 | 0.0102307 | 0.0098335 | 0.0102035 | 0.043142 |
| 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 | 1.678969 | 1.675055 | 1.679694 | 1.656866 | 1.670241 | 2.024306 |
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 5346739 285.6 8529671 455.6 8529671 455.6
Vcells 10521813 80.3 39910282 304.5 101881463 777.3
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 | 0.057347 | 0.0626875 | 0.0683666 | 0.0675210 | 0.0721960 | 0.116248 |
| 1 | t_tx_OP_y | 0.120752 | 0.1284740 | 0.1376355 | 0.1355545 | 0.1470275 | 0.189630 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 2.105638 | 2.049436 | 2.013199 | 2.00759 | 2.036505 | 1.631254 |
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 5346802 285.6 8529671 455.6 8529671 455.6
Vcells 10521855 80.3 39910282 304.5 101881463 777.3
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 | 0.056972 | 0.0605075 | 0.0666111 | 0.0658565 | 0.0699435 | 0.108408 |
| 1 | t_tx_OP_y | 0.117365 | 0.1224530 | 0.1325448 | 0.1310960 | 0.1419405 | 0.178648 |
| 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 | 2.060047 | 2.023766 | 1.989831 | 1.990631 | 2.029359 | 1.647923 |
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 5346865 285.6 8529671 455.6 8529671 455.6
Vcells 10523025 80.3 39910282 304.5 101881463 777.3
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 | 0.055723 | 0.0607015 | 0.0653311 | 0.064564 | 0.0689845 | 0.123239 |
| 1 | t_tx_OP_y | 0.110620 | 0.1182030 | 0.1264467 | 0.124564 | 0.1344270 | 0.157232 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 | 1.00000 |
| 1 | t_tx_OP_y | 1.985177 | 1.947283 | 1.935474 | 1.92931 | 1.948655 | 1.27583 |
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 5346928 285.6 8529671 455.6 8529671 455.6
Vcells 10523067 80.3 39910282 304.5 101881463 777.3
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 | 0.057257 | 0.0618795 | 0.0686627 | 0.0667695 | 0.0712090 | 0.125461 |
| 1 | t_tx_OP_y | 0.110634 | 0.1157625 | 0.1248591 | 0.1241510 | 0.1310625 | 0.160809 |
| 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 | 1.932235 | 1.870773 | 1.818442 | 1.859397 | 1.840533 | 1.281745 |
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 5346991 285.6 8529671 455.6 8529671 455.6
Vcells 10524009 80.3 39910282 304.5 101881463 777.3
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 | 0.055683 | 0.0590115 | 0.0643410 | 0.062696 | 0.066275 | 0.114057 |
| 1 | t_tx_OP_y | 0.115857 | 0.1198140 | 0.1286409 | 0.125181 | 0.139882 | 0.163571 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.00000 | 1.000000 | 1.000000 | 1.00000 | 1.000000 |
| 1 | t_tx_OP_y | 2.080653 | 2.03035 | 1.999363 | 1.996635 | 2.11063 | 1.434116 |
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 5347054 285.6 8529671 455.6 8529671 455.6
Vcells 10524051 80.3 39910282 304.5 101881463 777.3
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 | 0.057374 | 0.0622975 | 0.0677297 | 0.0664790 | 0.0712600 | 0.119041 |
| 1 | t_tx_OP_y | 0.116619 | 0.1209530 | 0.1307375 | 0.1300765 | 0.1405705 | 0.164055 |
| 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 | 2.032611 | 1.941539 | 1.930282 | 1.956656 | 1.972642 | 1.378139 |
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 5347117 285.6 8529671 455.6 8529671 455.6
Vcells 10524093 80.3 39910282 304.5 101881463 777.3
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 | 0.055697 | 0.0596275 | 0.0653551 | 0.0642965 | 0.0692240 | 0.108379 |
| 1 | t_tx_OP_y | 0.109868 | 0.1141450 | 0.1222848 | 0.1221065 | 0.1276875 | 0.170224 |
| 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 | 1.972602 | 1.914301 | 1.871082 | 1.899116 | 1.844555 | 1.570636 |
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 5347180 285.6 8529671 455.6 8529671 455.6
Vcells 10524135 80.3 39910282 304.5 101881463 777.3
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 | 0.057417 | 0.0615945 | 0.0670763 | 0.065023 | 0.0709420 | 0.120609 |
| 1 | t_tx_OP_y | 0.110178 | 0.1154895 | 0.1252119 | 0.123758 | 0.1332785 | 0.169451 |
| 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 | 1.918909 | 1.874997 | 1.866707 | 1.903296 | 1.878697 | 1.404961 |
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 5347243 285.6 8529671 455.6 8529671 455.6
Vcells 10523193 80.3 39910282 304.5 101881463 777.3
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 | 0.055494 | 0.0605835 | 0.0670083 | 0.065171 | 0.071558 | 0.100157 |
| 1 | t_tx_OP_y | 0.118505 | 0.1231200 | 0.1353603 | 0.132598 | 0.144270 | 0.183526 |
| 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 | 2.135456 | 2.032236 | 2.020053 | 2.034617 | 2.016127 | 1.832383 |
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 5347306 285.6 8529671 455.6 8529671 455.6
Vcells 10524616 80.3 39910282 304.5 101881463 777.3
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 | 0.057125 | 0.0605635 | 0.0662315 | 0.0643605 | 0.068340 | 0.119904 |
| 1 | t_tx_OP_y | 0.118209 | 0.1225260 | 0.1331453 | 0.1322005 | 0.142176 | 0.171543 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.0000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 |
| 1 | t_tx_OP_y | 2.069304 | 2.0231 | 2.010301 | 2.054063 | 2.080421 | 1.43067 |
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 5347369 285.6 8529671 455.6 8529671 455.6
Vcells 10524658 80.3 39910282 304.5 101881463 777.3
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 | 0.056160 | 0.060844 | 0.0659427 | 0.064927 | 0.0711255 | 0.110125 |
| 1 | t_tx_OP_y | 0.118343 | 0.122830 | 0.1339023 | 0.132397 | 0.1430455 | 0.183498 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.00000 |
| 1 | t_tx_OP_y | 2.107247 | 2.018769 | 2.030587 | 2.039167 | 2.01117 | 1.66627 |
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 5347432 285.6 8529671 455.6 8529671 455.6
Vcells 10524700 80.3 39910282 304.5 101881463 777.3
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 | 0.056323 | 0.0608125 | 0.0650540 | 0.0632835 | 0.0669205 | 0.104343 |
| 1 | t_tx_OP_y | 0.108495 | 0.1128955 | 0.1212958 | 0.1183870 | 0.1255740 | 0.166169 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.0000 | 1.000000 | 1.00000 | 1.00000 | 1.000000 | 1.000000 |
| 1 | t_tx_OP_y | 1.9263 | 1.856452 | 1.86454 | 1.87074 | 1.876465 | 1.592527 |
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 5347495 285.6 8529671 455.6 8529671 455.6
Vcells 10524826 80.3 39910282 304.5 101881463 777.3
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 | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.411295 | 0.497083 | 0.8821514 | 1.061525 | 1.099533 | 7.145404 |
| 1 | t_tx_OP_y | 0.921263 | 1.100072 | 1.1279309 | 1.104899 | 1.136356 | 1.453441 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 | 1.0000000 |
| 1 | t_tx_OP_y | 2.239908 | 2.213055 | 1.278614 | 1.040861 | 1.03349 | 0.2034092 |
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 5347558 285.6 8529671 455.6 8529671 455.6
Vcells 10524868 80.3 39910282 304.5 101881463 777.3
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 | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.414535 | 0.470233 | 0.8473406 | 0.6286205 | 1.107009 | 7.730513 |
| 1 | t_tx_OP_y | 0.900467 | 1.066302 | 1.0982466 | 1.1104705 | 1.123477 | 1.465273 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.000000 | 1.00000 | 1.00000 | 1.000000 | 1.0000000 |
| 1 | t_tx_OP_y | 2.172234 | 2.267602 | 1.29611 | 1.76652 | 1.014877 | 0.1895441 |
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 5347621 285.6 8529671 455.6 8529671 455.6
Vcells 10524910 80.3 39910282 304.5 101881463 777.3
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 | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 0.892535 | 1.027650 | 1.2045111 | 1.064426 | 1.082613 | 15.580454 |
| 2 | t_tx_OP_y_R | 0.414181 | 0.539297 | 0.8622419 | 1.069664 | 1.098082 | 1.172186 |
| 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 | 0.4640501 | 0.5247866 | 0.7158439 | 1.004921 | 1.014289 | 0.0752344 |
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 5347684 285.6 8529671 455.6 8529671 455.6
Vcells 10524952 80.3 39910282 304.5 101881463 777.3
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 | 0.403157 | 0.496001 | 0.8609197 | 0.6719925 | 1.108582 | 7.477739 |
| 1 | t_tx_OP_y | 0.825380 | 1.015748 | 1.0404657 | 1.0615775 | 1.076559 | 1.368619 |
| 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 | 2.047292 | 2.047876 | 1.208551 | 1.579746 | 0.9711144 | 0.1830258 |
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 5347747 285.7 8529671 455.6 8529671 455.6
Vcells 10527515 80.4 39910282 304.5 101881463 777.3
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 | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.416752 | 0.4953595 | 0.8527143 | 1.078172 | 1.127511 | 1.308924 |
| 1 | t_tx_OP_y | 0.936707 | 1.0874465 | 1.2634021 | 1.122507 | 1.150861 | 15.698562 |
| 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 | 2.247637 | 2.195267 | 1.481624 | 1.041121 | 1.020709 | 11.99349 |
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 5347810 285.7 8529671 455.6 8529671 455.6
Vcells 10527557 80.4 39910282 304.5 101881463 777.3
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 | 0.415826 | 0.5023805 | 0.8606416 | 1.095862 | 1.129530 | 1.208345 |
| 1 | t_tx_OP_y | 0.916296 | 1.0948055 | 1.2728903 | 1.108809 | 1.145771 | 16.209781 |
| 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 | 2.203556 | 2.179236 | 1.479002 | 1.011815 | 1.014378 | 13.41486 |
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 5347873 285.7 8529671 455.6 8529671 455.6
Vcells 10527599 80.4 39910282 304.5 101881463 777.3
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 | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 0.399634 | 0.4649385 | 0.8480145 | 0.622698 | 1.112753 | 7.305406 |
| 1 | t_tx_OP_y | 0.840513 | 0.9969675 | 1.0304693 | 1.048032 | 1.064135 | 1.309959 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 2 | t_tx_OP_y_R | 1.000000 | 1.0000 | 1.000000 | 1.000000 | 1.0000000 | 1.0000000 |
| 1 | t_tx_OP_y | 2.103207 | 2.1443 | 1.215155 | 1.683049 | 0.9563084 | 0.1793136 |
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 5347936 285.7 8529671 455.6 8529671 455.6
Vcells 10527641 80.4 39910282 304.5 101881463 777.3
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 | 0.914562 | 1.0463580 | 1.076590 | 1.064105 | 1.118907 | 1.383694 |
| 2 | t_tx_OP_y_R | 0.442452 | 0.5215435 | 1.023678 | 1.095954 | 1.143723 | 15.151286 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | t_tx_OP_y | 1.0000000 | 1.000000 | 1.0000000 | 1.00000 | 1.000000 | 1.00000 |
| 2 | t_tx_OP_y_R | 0.4837857 | 0.498437 | 0.9508519 | 1.02993 | 1.022179 | 10.94988 |
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_0.60.1 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] rappdirs_0.3.3 startup_0.15.0 labeling_0.4.2
[67] bitops_1.0-7 base64enc_0.1-3 boot_1.3-28
[70] gtable_0.3.0 DBI_1.1.1 markdown_1.1
[73] R6_2.5.1 lpSolveAPI_5.5.2.0-17.7 rle_0.9.2
[76] dplyr_1.0.7 fastmap_1.1.0 bit_4.0.4
[79] utf8_1.2.2 parallel_4.1.1 Rcpp_1.0.7
[82] vctrs_0.3.8 png_0.1-7 DEoptimR_1.0-9
[85] tidyselect_1.1.1 xfun_0.25 coda_0.19-4
Total processing time was 1.17 mins.
Reproducibility
To reproduce this report, do:
html <- matrixStats:::benchmark('t_tx_OP_y')
Copyright Henrik Bengtsson. Last updated on 2021-08-25 19:31:08 (+0200 UTC). Powered by RSP.