Reply To: using in-core and out-of-core mode

[peteroznewman]

You don't need to use this command, the solver will automatically use in-core if it finds there is sufficient free RAM for the model size.  After you hit Solve, you can read the Solver Output under the Solution Information folder and search for the word in-core to learn if the solver chose that method, but it is only easy to find if you used the Sparse Direct solver.

DISTRIBUTED SPARSE MATRIX DIRECT SOLVER.
  Number of equations =       28039,    Maximum wavefront =    342

  Process memory allocated for solver              =    31.709 MB
  Process memory required for in-core solution     =    16.745 MB
  Process memory required for out-of-core solution =     9.052 MB

  Total memory allocated for solver                =   141.429 MB
  Total memory required for in-core solution       =    77.605 MB
  Total memory required for out-of-core solution   =    38.401 MB

 *** NOTE ***                            CP =       9.812   TIME= 11:01:49
 The Distributed Sparse Matrix Solver is currently running in the        
 in-core memory mode.  This memory mode uses the most amount of memory   
 in order to avoid using the hard drive as much as possible, which most  
 often results in the fastest solution time.  This mode is recommended   
 if enough physical memory is present to accommodate all of the solver   
 data.                                                                   

If your model is much too large for in-core solving, install some more RAM or reduce the number of nodes in your model.

If the memory required for in-core solving seems to be just a small amount below the installed RAM minus the memory used by Windows, and the solver chose out-of-core solving, you can try restarting your computer to clean out the memory and not start any programs besides Ansys. If you are lucky, it will choose in-core.  If it does not, that is the only time it is useful to use the DSPOPTION,,INCORE command. However, though it may try to use in-core, it will automatically switch to out-of-core when it finds it needs more RAM.