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Provides functions to switch the BLAS/LAPACK optimized backend and change the number of threads without leaving the R session, which needs to be linked against the FlexiBLAS wrapper library.
See the installation section below for instructions on how to set a proper environment and install this package.
library(flexiblas)
# check whether FlexiBLAS is available
flexiblas_avail()
#> [1] TRUE
# get the current backend
flexiblas_current_backend()
#> [1] "OPENBLAS-OPENMP"
# list all available backends
flexiblas_list()
#> [1] "NETLIB" "__FALLBACK__" "BLIS-THREADS" "OPENBLAS-OPENMP"
#> [5] "BLIS-SERIAL" "ATLAS" "OPENBLAS-SERIAL" "OPENBLAS-THREADS"
#> [9] "BLIS-OPENMP"
# get/set the number of threads
flexiblas_set_num_threads(12)
flexiblas_get_num_threads()
#> [1] 12Example of GEMM benchmark for all the backends available:
library(flexiblas)
n <- 2000
runs <- 10
ignore <- "__FALLBACK__"
A <- matrix(runif(n*n), nrow=n)
B <- matrix(runif(n*n), nrow=n)
# load backends
backends <- setdiff(flexiblas_list(), ignore)
idx <- flexiblas_load_backend(backends)
# benchmark
timings <- sapply(idx, function(i) {
flexiblas_switch(i)
# warm-up
C <- A[1:100, 1:100] %*% B[1:100, 1:100]
unname(system.time({
for (j in seq_len(runs))
C <- A %*% B
})[3])
})
results <- data.frame(
backend = backends,
`timing [s]` = timings,
`performance [GFlops]` = (2 * (n / 1000)^3) / timings,
check.names = FALSE)
results[order(results$performance),]
#> backend timing [s] performance [GFlops]
#> 1 NETLIB 56.776 0.2818092
#> 5 ATLAS 5.988 2.6720107
#> 2 BLIS-THREADS 3.442 4.6484602
#> 8 BLIS-OPENMP 3.408 4.6948357
#> 4 BLIS-SERIAL 3.395 4.7128130
#> 6 OPENBLAS-SERIAL 3.206 4.9906425
#> 7 OPENBLAS-THREADS 0.773 20.6985770
#> 3 OPENBLAS-OPENMP 0.761 21.0249671Fedora 33+ ships R linked against FlexiBLAS. You can install multiple backends (atlas, blis-[serial|openmp|threads], openblas-[serial|openmp|threads]) as well as compile third-party libraries (such as MKL), and switch between them without leaving your R session using this package. If you are not running Fedora >= 33, you can set up a proper environment using docker.
The following command installs R and all the optimized BLAS/LAPACK backends shipped in Fedora (use sudo if appropriate):
Within the environment above, it can be installed from the official repos:
or install the release version from CRAN:
The installation from GitHub requires the remotes package.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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