README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# blazr <a href="https://r-staceans.github.io/blazr/"><img src="man/figures/logo.png" align="right" height="138" /></a>

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⚠️ **This package is a work in progress and is not yet ready for use.**

The goal of blazr is to provide R with a blazingly fast interface to multi-threading in Rust.

## Installation

Install the development version of `blazr` from GitHub with:

``` r
# install.packages("pak")
pak::pak("r-staceans/blazr")
```

## Example

Here's a simple example, computing the sum of a vector of integers, using multiple threads:

```{r example}
library(blazr)

create_int_vector <- function(n) {
  set.seed(42)
  sample.int(100, n, replace = TRUE)
}

n <- 1e8

x <- create_int_vector(n)

blazr::sum_with_threads(
  x,
  n = 2L
)
```

## Benchmarking

When running this sum against very large numbers, we can see the performance benefits of using multiple threads:

```{r benchmark}
library(bench)
library(ggplot2)

results <- bench::press(
  size = c(1e7, 1e8, 1e9),
  {
    x = create_int_vector(n)
    bench::mark(
      single_thread = {
        blazr::sum_with_threads(
          x,
          n = 1L
        )
      },
      multi_thread = {
        blazr::sum_with_threads(
          x,
          n = 4L
        )
      }
    )
  })

ggplot2::autoplot(results)
```