snoption

Mapdl.snoption(rangefact='', blocksize='', robustlev='', compute='', solve_info='', **kwargs)

Specifies Supernode (SNODE) eigensolver options.

APDL Command: SNOPTION

Parameters:

rangefact

Factor used to control the range of eigenvalues computed for each supernode. The value of RangeFact must be a number between 1.0 and 5.0. By default the RangeFact value is set to 2.0, which means that all eigenvalues between 0 and 2*FREQE are computed for each supernode (where FREQE is the upper end of the frequency range of interest as specified on the MODOPT command). As the RangeFact value increases, the eigensolution for the SNODE solver becomes more accurate and the computational time increases.

blocksize

BlockSize to be used when computing the final eigenvectors. The value of Blocksize must be either MAX or a number between 1 and NMODE, where NMODE is the number of modes to be computed as set on the MODOPT command. Input a value of MAX to force the algorithm to allocate enough memory to hold all of the final eigenvectors in memory and, therefore, only read through the file containing the supernode eigenvectors once. Note that this setting is ONLY recommended when there is sufficient physical memory on the machine to safely hold all of the final eigenvectors in memory.

robustlev

Parameter used to control the robustness of the SNODE eigensolver. The value of RobustLev must be a number between 0 and 10. Lower values of RobustLev allow the eigensolver to run in the most efficient manner for optimal performance. Higher values of RobustLev often slow down the performance of the eigensolver, but can increase the robustness; this may be desirable if a problem is detected with the eigensolver or its eigensolution.

compute

Key to control which computations are performed by the Supernode eigensolver:

EVALUE - The eigensolver computes only the eigenvalues.

EVECTOR - The eigensolver computes only the eigenvectors

(must be preceded by a modal analysis where the eigenvalues were computed using the Supernode eigensolver).

BOTH - The eigensolver computes both the eigenvalues and

eigenvectors in the same pass (default).

solve_info

Solver output option:

OFF - Turns off additional output printing from the Supernode eigensolver (default).

PERFORMANCE - Turns on additional output printing from the

Supernode eigensolver, including a performance summary and a summary of file I/O for the Supernode eigensolver. Information on memory usage during assembly of the global matrices (that is, creation of the Jobname.FULL file) is also printed with this option.

Notes

This command specifies options for the Supernode (SNODE) eigensolver.

Setting RangeFact to a value greater than 2.0 will improve the accuracy of the computed eigenvalues and eigenvectors, but will often increase the computing time of the SNODE eigensolver. Conversely, setting RangeFact to a value less than 2.0 will deteriorate the accuracy of the computed eigenvalues and eigenvectors, but will often speedup the computing time of the SNODE eigensolver. The default value of 2.0 has been set as a good blend of accuracy and performance.

The SNODE eigensolver reads the eigenvectors and related information for each supernode from a file and uses that information to compute the final eigenvectors. For each eigenvalue/eigenvector requested by the user, the program must do one pass through the entire file that contains the supernode eigenvectors. By choosing a BlockSize value greater than 1, the program can compute BlockSize number of final eigenvectors for each pass through the file. Therefore, smaller values of BlockSize result in more I/O, and larger values of BlockSize result in less I/O. Larger values of BlockSize also result in significant additional memory usage, as BlockSize number of final eigenvectors must be stored in memory. The default Blocksize of min(NMODE,40) is normally a good choice to balance memory and I/O usage.

The RobustLev field should only be used when a problem is detected with the accuracy of the final solution or if the Supernode eigensolver fails while computing the eigenvalues/eigenvectors. Setting RobustLev to a value greater than 0 will cause the performance of the eigensolver to deteriorate. If the performance deteriorates too much or if the eigensolver continues to fail when setting the RobustLev field to higher values, then switching to another eigensolver such as Block Lanczos or PCG Lanczos is recommended.

Setting Compute = EVALUE causes the Supernode eigensolver to compute only the requested eigenvalues. During this process a Jobname.SNODE file is written; however, a Jobname.MODE file is not written. Thus, errors will likely occur in any downstream computations that require the Jobname.MODE file (for example, participation factor computations, mode superpostion transient/harmonic analysis, PSD analysis). Setting Compute = EVECTOR causes the Supernode eigensolver to compute only the corresponding eigenvectors. The Jobname.SNODE file and the associated Jobname.FULL file are required when requesting these eigenvectors. In other words, the eigenvalues must have already been computed for this model before computing the eigenvectors. This field can be useful in order to separate the two steps (computing eigenvalues and computing eigenvectors).