snow-parallel              package:snow              R Documentation

_H_i_g_h_e_r _L_e_v_e_l _S_N_O_W _F_u_n_c_t_i_o_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     Parallel versions of 'apply' and related functions.

_U_s_a_g_e:

     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)

_A_r_g_u_m_e_n_t_s:

      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

_D_e_t_a_i_l_s:

     '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 <URL:
     http://www.stat.uiowa.edu/~luke/R/cluster/cluster.html>.

_E_x_a_m_p_l_e_s:

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

