Hi Florian,
just a guess, but couldn't it be that the multiplication of very small
values leads to FP underflow exceptions which have to be handled by BLAS
in a less efficient way than "normal" multiplications handled by SIMD
instructions ?
Best regards,
Hilmar
On 19/11/2019 15:09, Florian Gerber wrote:
Hi,
I experience surprisingly large timing differences for the
multiplication of matrices of the same dimension. An example is given
below. How can this be explained?
I posted the question on Stackoverflow:
https://stackoverflow.com/questions/58886111/r-why-is-matrix-product-slower-when-matrix-has-very-small-values
Somebody could reproduce the behavior but I did not get any useful
explanations yet.
Many thanks for hints!
Florian
## disable openMP
library(RhpcBLASctl); blas_set_num_threads(1); omp_set_num_threads(1)
A <- exp(-as.matrix(dist(expand.grid(1:60, 1:60))))
summary(c(A))
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 0.000000 0.000000 0.000000 0.001738 0.000000 1.000000
B <- exp(-as.matrix(dist(expand.grid(1:60, 1:60)))*10)
summary(c(B))
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 0.0000000 0.0000000 0.0000000 0.0002778 0.0000000 1.0000000
identical(dim(A), dim(B))
## [1] TRUE
system.time(A %*% A)
# user system elapsed
# 2.387 0.001 2.389
system.time(B %*% B)
# user system elapsed
# 21.285 0.020 21.310
sessionInfo()
# R version 3.6.1 (2019-07-05)
# Platform: x86_64-pc-linux-gnu (64-bit)
# Running under: Linux Mint 19.2
# Matrix products: default
# BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
# LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
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--
Dr. Hilmar Berger, MD
Max Planck Institute for Infection Biology
Charitéplatz 1
D-10117 Berlin
GERMANY
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E-Mail: ber...@mpiib-berlin.mpg.de
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