bdblockmult_vector: Block matrix-vector multiplication with Delayed Array Object

In BigDataStatMeth: Statistical Methods and Algorithms for Big Data

Block matrix-vector multiplication with Delayed Array Object

Description

This function performs a block matrix-vector multiplication with R-Objects or Delayed Arrays

Usage

bdblockmult_vector(
  A,
  b,
  block_size = 128,
  paral = TRUE,
  threads = NULL,
  outfile = "tmp_blockmult_vector.hdf5",
  onmemory = FALSE
)

Arguments

A	a double matrix.
b	a double vector or array.
block_size	(optional, defalut = 128) block size to make matrix multiplication, if 'block_size = 1' no block size is applied (size 1 = 1 element per block)
paral,	(optional, default = TRUE) if paral = TRUE performs parallel computation else performs seria computation
threads	(optional) only if bparal = true, number of concurrent threads in parallelization if threads is null then threads = maximum number of threads available
outfile	(optional) file name to work with hdf5 if we are working with big matrix in disk.
onmemory	(optional) if onmemory = TRUE the multiplication is forced to execute in memory

Value

numerical matrix

Examples

# with numeric matrix

k <- 100
n <- 400
A <- matrix(rnorm(n*k), nrow=n, ncol=k)
B <- sample(1:100,100, replace = TRUE);

res <- bdblockmult_vector(A, B, 128, TRUE)

BigDataStatMeth documentation built on March 30, 2022, 1:07 a.m.