Why a SYMMETRIC type option for the Extended Eigensolver?

[Vishnu]

The extended eigensolver routines: `mkl_sparse_?_ev` allow for specifying the type of the input matrix as SYMMETRIC or GENERAL. But since the routine only accepts symmetric matrices any way, what, if any difference does either option make?

(The documentation says that the matrix 'A' is symmetric)

I tried both and get roughly the same time on both.

Is it that I can use an input sparse matrix with half the amount of data if I set it to the SYMMETRIC type?

[Gennady_F_Intel]

yes, you can use an input sparse matrix with half the amount of data by setting 

sparse_matrix_type_t  type == SPARSE_MATRIX_TYPE_SYMMETRIC

[Vishnu]

Okay, thanks for that! It would be nice if this information were present in the documentation, so that users know when to use the option.

So then does this come with a computational cost? I ask because my current priority is speed and not space. Also because examining some back-traces seem to show the usage of some 'transpose' and 'symmetric-to-general' conversion routines when using the SYMMETRIC option, and I'm assuming that is not cheap (especially for large matrices).

[IntelSupport]

Hello Vishnu,

Thank you for posting your question on this Intel® Community.

To better assist you, please submit your question on the Intel® Developer Zone.

https://software.intel.com/content/www/us/en/develop/home.html

You can also submit tickets through the customer portal at http://www.intel.com/supporttickets for support.

Wanner G.

Intel Customer Support Technician

[Vishnu]

> To better assist you, please submit your question on the Intel® Developer Zone.

> https://software.intel.com/content/www/us/en/develop/home.html

I am not sure where exactly you mean. That link does not take me to anywhere I can make a post.