snow-parallel {snow} | R Documentation |

## Higher Level SNOW Functions

### Description

Parallel versions of `apply`

and related functions.

### Usage

parLapply(cl, x, fun, ...)
parSapply(cl, X, FUN, ..., simplify = TRUE, USE.NAMES = TRUE)
parApply(cl, X, MARGIN, FUN, ...)
parRapply(cl, x, fun, ...)
parCapply(cl, x, fun, ...)
parMM(cl, A, B)

### Arguments

`cl` |
cluster object |

`fun` |
function or character string naming a function |

`X` |
array to be used |

`x` |
matrix to be used |

`FUN` |
function or character string naming a function |

`MARGIN` |
vector specifying the dimensions to use. |

`simplify` |
logical; see `sapply` |

`USE.NAMES` |
logical; see `sapply` |

`...` |
additional arguments to pass to standard function |

`A` |
matrix |

`B` |
matrix |

### Details

`parLapply`

, `parSapply`

, and `parApply`

are parallel
versions of `lapply`

, `sapply`

, and `apply`

.

`parRapply`

and `parCapply`

are parallel row and column
`apply`

functions for a matrix `x`

; they may be slightly
more efficient than `parApply`

.

`parMM`

is a very simple(minded) parallel matrix multiply;
it is intended as an illustration.

For more details see
http://www.stat.uiowa.edu/~luke/R/cluster/cluster.html.

### Examples

## Not run:
cl <- makeSOCKcluster(c("localhost","localhost"))
parSapply(cl, 1:20, get("+"), 3)
## End(Not run)

[Package

*snow* version 0.2-1

Index]