Why is matrix product slower when matrix has very small values?

I create two matrices A and B of the same dimension. A contains larger values than B. The matrix multiplication A %*% A is about 10 times faster than B %*% B.

Why is this?

## 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

The question could be related to R: base::chol() slows down when matrix contains many small entries.