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December 15, 2023 10:20
Test performance of Intel MKL on matrix operations
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# Set MKL threads if Revolution R Open or Revolution R Enterprise is available | |
if(require("RevoUtilsMath")){ | |
setMKLthreads(4) | |
} | |
# Initialization | |
set.seed (1) | |
m <- 10000 | |
n <- 5000 | |
A <- matrix (runif (m*n),m,n) | |
# Matrix multiply | |
system.time (B <- crossprod(A)) | |
# Cholesky Factorization | |
system.time (C <- chol(B)) | |
# Singular Value Deomposition | |
m <- 10000 | |
n <- 2000 | |
A <- matrix (runif (m*n),m,n) | |
system.time (S <- svd (A,nu=0,nv=0)) | |
# Principal Components Analysis | |
m <- 10000 | |
n <- 2000 | |
A <- matrix (runif (m*n),m,n) | |
system.time (P <- prcomp(A)) | |
# Linear Discriminant Analysis | |
library('MASS') | |
g <- 5 | |
k <- round (m/2) | |
A <- data.frame (A, fac=sample (LETTERS[1:g],m,replace=TRUE)) | |
train <- sample(1:m, k) | |
system.time (L <- lda(fac ~., data=A, prior=rep(1,g)/g, subset=train)) |
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Revobase should be replaced by RevoUtilsMath.