# Parallelize 'BiocParallel' functions

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The futurize package allows you to easily turn sequential code into parallel code by piping the sequential code to the `futurize()` function. Easy!

# TL;DR

    library(futurize)
    plan(multisession)
    library(BiocParallel)

    slow_fcn <- function(x) {
      Sys.sleep(0.1)  # emulate work
      x^2
    }

    xs <- 1:1000
    ys <- bplapply(xs, slow_fcn) |> futurize()

# Introduction

This vignette demonstrates how to use this approach to parallelize functions such as `bplapply()`, `bpmapply()`, and `bpvec()` in the BiocParallel package. For example, consider the `bplapply()` function. It works like base-R `lapply()`, but uses the BiocParallel framework to process the tasks concurrently. It is commonly used something like:

    library(BiocParallel)
    xs <- 1:1000
    ys <- bplapply(xs, slow_fcn)

The parallel backend is controlled by the `BiocParallel::register()`, similar to how we use `future::plan()` in futureverse. We can use the futurize package to tell BiocParallel to hand over the orchestration of parallel tasks to futureverse. All we need to do is to pass the expression to `futurize()` as in:

    library(futurize)
    library(BiocParallel)
    xs <- 1:1000
    ys <- bplapply(xs, slow_fcn) |> futurize()

This will distribute the calculations across the available parallel workers, given that we have set parallel workers, e.g.

    plan(multisession)

The built-in `multisession` backend parallelizes on your local computer and it works on all operating systems. There are other parallel backends to choose from, including alternatives to parallelize locally as well as distributed across remote machines, e.g.

    plan(future.mirai::mirai_multisession)

and

    plan(future.batchtools::batchtools_slurm)

# Supported Functions

The `futurize()` function supports parallelization of all BiocParallel functions that take argument `BPPARAM`. Specifically,

- `bplapply()` and `.bplapply_impl()`
- `bpmapply()` and `.bpmapply_impl()`
- `bpvec()`
- `bpaggregate()`

The following functions are currently not supported:

- `bpiterate()` - technically supported, but because this function does not support using `DoparParam()` with it, it effectively does not work with `futurize()`
- `bpvectorize()`
- `register()`