`cluster_call()` executes the code on each worker and returns the results; `cluster_send()` executes the code ignoring the result. Jobs are submitted to workers in parallel, and then we wait until they're complete.

## Arguments

- cluster
A cluster.

- code
An expression to execute on each worker.

- simplify
Should the results be simplified from a list? * `TRUE`: simplify or die trying. * `NA`: simplify if possible. * `FALSE`: never try to simplify, always leaving as a list.

`code` must return a vector of length one in order for simplification to succeed.

- ptype
If `simplify` is `TRUE`, use `ptype` to enforce the desired output type.

## Examples

```
cl <- default_cluster()
#> Initialising default cluster of size 2
# Run code on each cluster and retrieve results
cluster_call(cl, Sys.getpid())
#> [[1]]
#> [1] 5814
#>
#> [[2]]
#> [1] 5821
#>
cluster_call(cl, runif(1))
#> [[1]]
#> [1] 0.4918143
#>
#> [[2]]
#> [1] 0.7023157
#>
# use ptype to simplify
cluster_call(cl, runif(1), simplify = TRUE)
#> [1] 0.7602377 0.5912457
# use cluster_send() to ignore results
cluster_send(cl, x <- runif(1))
cluster_call(cl, x, simplify = TRUE)
#> [1] 0.1751519 0.8426909
```