VERY EARLY DEVELOPMENT!!! The idea is to pass matrices/vectors from R to C++, write pure C++/Blaze code for the computation, and then export the result back to R with the proper data structures.
APACHE-2.0 License
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
VERY EARLY STAGE PACKAGE!!!
The goal of cpp11blaze is to provide a novel approach to use the Blaze C++ library by using the header-only cpp11 R package and to simplify things for the end-user.
The idea is to pass matrices/vectors from R to C++, write pure C++/Blaze code for the computation, and then export the result back to R with the proper data structures.
This follows from the same goals as cpp11:
If this software is useful to you, please consider donating on
Buy Me A Coffee. All donations will
be used to continue improving cpp11blaze
.
You can install the development version of cpp11blaze from GitHub:
remotes::install_github("pachadotdev/cpp11blaze")
I have provided a package template for RStudio that also works with VS Code.
The idea of this package is to be naive and simple (like me).
From RStudio/VSCode create a new project and run:
cpp11blaze::pkg_template()
Then follow the instructions from the README.
The vignettes contains detailed examples that I use to test cpp11blaze
,
these include Ordinary Least Squares.
Blaze supports OpenBLAS, Intel MKL, and the Accelerate framework (Mac). You can install OpenBLAS on Debian-based systems with:
sudo apt-get install libopenblas-dev
You can also use other commands for your specific operating system.
To verify that R is using OpenBLAS, you can run sessionInfo()
after restarting
R to check the BLAS/LAPACK libraries in use:
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0