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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
