The “parCapply” Function in R

  • Package: parallel

  • Purpose: Apply a function to the columns of a matrix using a cluster for parallel processing.

  • General class: Parallel computing

  • Required argument(s):

    • cl: A cluster object created using the makeCluster function.

    • x: A matrix or array.

    • FUN: The function to be applied to each column of the matrix.

  • Notable optional arguments:

    • ...: Additional arguments to be passed to the applied function FUN.

  • Example:

  • # Load the parallel package
    library(parallel)

    # Create a matrix
    mat <- matrix(1:25, nrow = 5)

    # Create a cluster with 2 nodes
    cl <- makeCluster(2)

    # Apply a function to each column using parallel processing
    result <- parCapply(x = mat, FUN = mean, cl = cl)

    # Stop the cluster
    stopCluster(cl)

    # Print the result
    print(result)

  • In this example, we create a matrix mat, then create a cluster cl with 2 nodes using the makeCluster function. We then use parCapply to apply the mean function to each column of the matrix using parallel processing with the specified cluster. Finally, we print the result and stop the cluster using stopCluster.

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The “clusterApply” Function in R

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The “parRapply” Function in R