Parallel computing

quanteda takes advantage of parallel computing through the TBB (Threading Building Blocks) library to speed up computations. This guide provides step-by-step instructions on how to set up your system for using Quanteda with parallel capabilities on Windows, macOS, and Linux.

For Windows Users

Install RTools

Download and install RTools from RTools download page.
During installation, ensure you select the option to add RTools to the system path.

Check Installation

Open an R session and check that RTools is correctly configured:
```
find.package("pkgbuild")
```

For macOS users

Opening the Terminal

To open the terminal on macOS, press Cmd+Space to open Spotlight, type “Terminal”, and press enter. Alternatively, you can find the Terminal in /Applications/Utilities/.

Install required tools and libraries

Install XCode Command Line Tools
- Type the following command in the terminal:
```
xcode-select --install
```

Install Homebrew

If Homebrew is not installed, run:

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

Follow the on-screen instructions.

Install TBB and pkg-config
- After installing Homebrew, run:
```
brew install tbb pkg-config
```
Install gfortran
- Required for compiling Fortran code, install using Homebrew:
```
brew install gcc
```

For Linux users

Opening the terminal

To open the terminal in Linux, you can usually use Ctrl+Alt+T, or search for “Terminal” in your system’s application launcher.

Install TBB

For Fedora, CentOS, RHEL:
```
sudo yum install tbb-devel
```
For Debian and Ubuntu:
```
sudo apt install libtbb-dev
```

Installing quanteda from CRAN

After setting up the required tools and libraries, install quanteda from CRAN:

install.packages("quanteda")

Parallelisation functions properly if you receive a message detailing the number of threads used for parallel computing after loading quanteda.

library(quanteda)
# Package version: 4.0.2
# Unicode version: 15.1
# ICU version: 74.1
# Parallel computing: 20 of 20 threads used.
# See https://quanteda.io for tutorials and examples.

Kenneth Benoit and Stefan Müller