[R] efficiently multiply different matrices in 3-d array with different vectors?

[arun]

HI,
Tx for the fast method.
dim(Rt)
#b 
#2 
 dim(X)
#[1]     2 50000


Is it possible to obtain the same result as X without converting X to R?   

According to OP "..... which will give me a (two-dimensional) array or matrix of dimension n x 
p with the i'th row storing the above.
"

A.K.





----- Original Message -----
From: "Suzen, Mehmet" <msuzen at gmail.com>
To: arun <smartpink111 at yahoo.com>
Cc: Ranjan Maitra <maitra.mbox.ignored at inbox.com>; R help <r-help at r-project.org>
Sent: Saturday, December 29, 2012 1:19 PM
Subject: Re: [R] efficiently multiply different matrices in 3-d array with different vectors?

What I had in mind was a tensor multiplication.
I think,  using tensor arithmetic for multidimensional arrays looks
more compacts
and efficient (~ 2-3 times). I am guessing that performance will be much more
pronounced for n-D arrays (n>3).

# Component Wise
set.seed(14)
Z<-array(sample(1:1000000,800000,replace=TRUE),dim=c(50000,2,8))
set.seed(21)
Y<-matrix(sample(1:400000,400000,replace=TRUE),nrow=8)
system.time(X<-do.call(cbind,lapply(seq_len(dim(Z)[1]),function(i)
Z[i,,]%*%Y[,i])))
#   user  system elapsed
#   0.58    0.00    0.58
R<-cbind(sum(X[1,]), sum(X[2,]))
# Tensor multiply
library(tensorA)
set.seed(14)
Zt <-to.tensor(sample(1:1000000,800000,replace=TRUE), c(a=50000, b=2, c=8))
set.seed(21)
Yt <-to.tensor(sample(1:400000,400000,replace=TRUE), c(c=8, a=50000))
system.time(Rt<-Zt %e% Yt)
#   user  system elapsed
#  0.124   0.000   0.126
# correct results?
R
#            [,1]         [,2]
#[1,] 4.00595e+16 3.997387e+16
Rt
#[1] 4.005950e+16 3.997387e+1