76 lines
2.1 KiB
R
76 lines
2.1 KiB
R
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# source: https://gist.github.com/andrie/24c9672f1ea39af89c66#file-rro-mkl-benchmark-r
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runs = 10
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results = data.frame(name=character(), time=numeric())
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cat(c("Runs :", runs, "\n"))
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# Initialization
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set.seed (1)
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m <- 10000
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n <- 5000
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A <- matrix (runif (m*n),m,n)
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cat("Matrix Multiply : ")
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cumulate = 0
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for (i in 1:runs)
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cumulate = cumulate + as.numeric(system.time (B <- crossprod(A))[3])
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results = rbind(results, data.frame(name="Matrix Multiply",
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time=cumulate/runs))
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cat(c(cumulate/runs, "\n"))
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cat("Cholesky Factorization : ")
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cumulate = 0
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for (i in 1:runs)
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cumulate = cumulate + as.numeric(system.time (C <- chol(B))[3])
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results = rbind(results, data.frame(name="Cholesky Factorization",
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time=cumulate/runs))
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cat(c(cumulate/runs, "\n"))
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cat("Singular Value Deomposition : ")
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m <- 10000
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n <- 2000
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A <- matrix (runif (m*n),m,n)
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cumulate = 0
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for (i in 1:runs)
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cumulate = cumulate + as.numeric(system.time (S <- svd (A,nu=0,nv=0))[3])
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results = rbind(results, data.frame(name="Singular Value Deomposition",
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time=cumulate/runs))
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cat(c(cumulate/runs, "\n"))
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cat("Principal Components Analysis : ")
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m <- 10000
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n <- 2000
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A <- matrix (runif (m*n),m,n)
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cumulate = 0
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for (i in 1:runs)
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cumulate = cumulate + as.numeric(system.time (P <- prcomp(A))[3])
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results = rbind(results, data.frame(name="Principal Components Analysis",
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time=cumulate/runs))
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cat(c(cumulate/runs, "\n"))
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cat("Linear Discriminant Analysis : ")
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library('MASS')
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g <- 5
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k <- round (m/2)
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A <- data.frame (A, fac=sample (LETTERS[1:g],m,replace=TRUE))
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train <- sample(1:m, k)
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cumulate = 0
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for (i in 1:runs)
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cumulate = cumulate + as.numeric(system.time (L <- lda(fac ~., data=A, prior=rep(1,g)/g, subset=train))[3])
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results = rbind(results, data.frame(name="Linear Discriminant Analysis",
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time=cumulate/runs))
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cat(c(cumulate/runs, "\n"))
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attr(results, "runs") = runs
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saveRDS(results, paste0("test-revolution-", ifelse(exists("blasLibName"), blasLibName, ""), ".rds"))
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