The following steps will show you how to use multiple chips in
your computer when using R.
(1) In order to use multiple chips, you must use the R package
'parallel'.
(2) Create a directory to store the needed files. We will assume that
this directory is called 'test'.
(4) The file a1dual.R
runs GenMatch() using all or some of the chips available in your
computer. Remember that in order to use multiple chips, you must load
the 'parallel' library. The line 'cl <- NCPUS()' creates the cluster
object by calling the function 'NCPUS()', and this object is then
passed to 'GenMatch()' via the 'cluster' option.
The function 'NCPUS()' is in the file AutoCluster4.R,
which you must source at the beginning of the file. If the file is in
your working directory, you can source it by just typing
'source("AutoCluster4.R")'.
The 'NCPUS()' function can be called with or without arguments. When
the function 'NCPUS()' is executed with no arguments, the number of
chips available in the computer is automatically detected and a
cluster is created using as many chips as there are
available. Alternatively, the user can specify the precise number of
chips to be used by passing the number of chips as an argument. For
example, 'cl <- NCPUS(nchips=4)' would create a cluster using exactly
four chips in the computer (assuming that the computer does have four
chips). If your computer had two chips and you wanted to create a
cluster using both chips, you would type 'cl <- NCPUS(nchips=2)'.
(5) Done. The file a1dual.R
will run 'GenMatch()' using multiple chips in your computer.
Instructions for Windows
In Windows, the 'NCPUS()' function must be called with an
argument. The user must specify the precise number of chips to be
included in the cluster by passing the number of chips as an argument
to the function. For example, 'cl <- NCPUS(nchips=4)' would create a
cluster using exactly four chips in the computer (assuming that the
computer does have four chips). If your computer had two chips and you
wanted to create a cluster using both chips, you would type 'cl <-
NCPUS(nchips=2)'.