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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!
library(futurize)
plan(multisession)
library(seriation)
o <- seriation::seriate_best(d_supreme) |> futurize()
The seriation package provides functions for ordering objects using seriation, ordination techniques for reordering matrices, dissimilarity matrices, and dendrograms.
Example adopted from help("seriate_best", package = "seriation"):
library(futurize)
plan(multisession)
library(seriation)
data(SupremeCourt)
d_supreme <- as.dist(SupremeCourt)
o <- seriate_best(d_supreme, criterion = "AR_events") |> futurize()
print(o)
This will parallelize the computations, given that we have set up parallel workers, e.g.
plan(multisession)
The built-in multisession backend parallelizes on your local
computer and 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)
The following seriation functions are supported by futurize():
seriate_best()seriate_rep()