82 lines
2.1 KiB
R
82 lines
2.1 KiB
R
# source: CRAN gcbd package
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size = c(100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1250, 1500, 1750, 2000, 2500, 3000, 3500, 4000, 4500, 5000)
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runs = c( 50, 50, 50, 50, 50, 50, 50, 50, 50, 30, 30, 30, 30, 20, 20, 5, 5, 5, 5, 5)
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meanTrim = 0.1
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results = data.frame(t1=numeric(), t2=numeric(), t3=numeric(), t4=numeric())
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library(Matrix)
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# functions
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getMatrix <- function(N) {
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a <- rnorm(N*N)
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dim(a) <- c(N,N)
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invisible(gc())
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invisible(a)
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}
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matmultBenchmark <- function(N, n, trim=0.1) {
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a <- getMatrix(N)
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traw <- replicate(n, system.time(crossprod(a))[3])
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tmean <- mean(traw,trim=trim)
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}
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qrBenchmark <- function(N, n, trim=0.1) {
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a <- getMatrix(N)
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traw <- replicate(n, system.time(qr(a, LAPACK=TRUE))[3])
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tmean <- mean(traw,trim=trim)
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}
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svdBenchmark <- function(N, n, trim=0.1) {
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a <- getMatrix(N)
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traw <- replicate(n, system.time(svd(a))[3])
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tmean <- mean(traw,trim=trim)
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}
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luBenchmark <- function(N, n, trim=0.1) {
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a <- getMatrix(N)
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traw <- replicate(n, system.time(lu(a))[3])
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tmean <- mean(traw,trim=trim)
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}
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# Initialization
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set.seed (1)
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cat(paste0("Mean trim : ", meanTrim, "\n"))
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for (i in 1:length(size))
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{
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n = size[i]
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r = runs[i]
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cat(paste0("Size : ", n, "\n"))
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cat(paste0("Runs : ", r, "\n"))
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t1 = matmultBenchmark(n, r, meanTrim)
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cat(paste0("Matrix Multiply : ", t1, "\n"))
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t2 = qrBenchmark(n, r, meanTrim)
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cat(paste0("QR Decomposition : ", t2, "\n"))
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t3 = svdBenchmark(n, r, meanTrim)
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cat(paste0("Singular Value Deomposition : ", t3, "\n"))
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t4 = luBenchmark(n, r, meanTrim)
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cat(paste0("Triangular Decomposition : ", t4, "\n"))
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results = rbind(results, data.frame(t1=t1, t2=t2, t3=t3, t4=t4))
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}
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colnames(results) = c("Matrix Multiply", "QR Decomposition",
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"Singular Value Deomposition", "Triangular Decomposition")
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attr(results, "size") = size
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attr(results, "runs") = runs
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attr(results, "meanTrim") = meanTrim
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saveRDS(results, paste0("test-gcbd-", ifelse(exists("blasLibName"), blasLibName, ""), ".rds"))
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