# Parallel Execution for Confidence Intervals

#### Justin Kamerman

#### 2024-08-27

To leverage multicore processors to speed up calcualtion of confidence intervals, use the `parallel` package to create a cluster and attach the `qfasa.parallel.cluster` option.

The cluster can be used for multiple invocations of `beta.meths.CI()` but should be shut down when work is complete to free up resources.

## Set Number of Cores

For maximum speedup, set the `qfasa.parallel.numcores` option to the total number of cores on your computer. The number of cores can be determined using the `detectCores()` function.

    parallel::detectCores()

    ## [1] 20

## Create Cluster

    options(qfasa.parallel.numcores = 8)
    options(qfasa.parallel.cluster = parallel::makeCluster(getOption('qfasa.parallel.numcores'),
                                                           type='FORK'))
    #
    # Note that if using windows, do not include type='FORK'.

## Confidence Intervals

No change is required to the `conf.meth()` call. The implementation will automatically detect the cluster and use it to parallelize the bootstrap iterations.

## Shut Down Cluster

    parallel::stopCluster(getOption('qfasa.parallel.cluster'))

## Portability

Parallel execution has been tested on Ubuntu Linux, AWS Linux, and MacOS platforms only.