speed issue with mxRun

Dear All,

I am writing on behalf of a user of our local cluster.

The OpenMX install is fairly recent (just with source('https://openmx.ssri.psu.edu/getOpenMx.R' in R). The script in question is rather long and starts with loading OpenMX:

require(OpenMx)

and subsequently snowfall:

library(snowfall)
sfInit(parallel = T, cpus = 64)
sfLibrary(OpenMx)

Apparently, OpenMx is recognized correctly as snowfalls 'sfLibrary' - during the setup all cores are utilised. When fitting models a CPU usage > 100 % is observed, albeit not all cores are used in average (as the individual fits are short). However, hitting a mxRun function step takes several days to execute.

The model in question is setup like:

HetModel <- mxModel("Heterogeneity Model",
+ funMG)

where 'funMG' is a mxFitFunctionMultigroup-object.

printing HetModel gives:

MxModel 'Heterogeneity Model'
type : default
$matrices : NULL
$algebras : NULL
$constraints : NULL
$intervals : NULL
$latentVars : none
$manifestVars : none
$data : NULL
$submodels : 'ModelForSample1', 'ModelForSample2', ...
$expectation : NULL
$fitfunction : MxFitFunctionMultigroup
$compute : NULL
$independent : FALSE
$options :
$output : FALSE

with a total of at least 200 submodels (hence the '...')

Is there any way to speed up the execution of mxRun? E.g. by dividing the task? (I tried setting useSocket = T, without effect).

Any pointer is appreciated.

Thanks a lot,
Christian