Response #1: 2005-08-09

General

1. Is dense linear algebra a performance bottleneck in your applications?
Yes

2. How often do your applications use the arithmetic precisions listed below:

3. What dense matrix sizes are most important or time-consuming for your application?
100,000s X 100,000s

4. Does your application come close to, or run out of memory on important problems?
No

5. Number of processors used for your application:

6. Which architectures do you use or intend to use in the next three years?
Distributed-memory

9. Do your applications solve linear algebra problems of the type?
Generalized eigenvalue, Non-symmetric eigenvalue

LAPACK Usage

1. Do you use LAPACK (or a vendor version of LAPACK )?
Yes

4. If you use LAPACK, do you use a vendors version or one obtained directly from Netlib?
Netlib

5. If you have used both a vendors version of LAPACK and Netlibs, how do the two versions compare?
Vendor faster but Vendor is incomplete or undefined API (Lapack 1? 2? 3?)

6. Do your applications make direct LAPACK calls?
Yes

7. Do your applications use libraries which depend on LAPACK?
Yes

8. Do your applications use a higher-level interface to LAPACK?
Yes

9. If you answered yes above, which higher-level interfaces do you use?
R

10. Is the LAPACK procedure interface a barrier to more extensive use?
No

11. From which languages do you call LAPACK routines?
C, C++, Fortran 77, Fortran 90/95

14. If you have installed LAPACK yourself, how could the installation process be improved?
Place in autoconfig construct as a package in itself Place in autoconfig construct with scalapack, lapack, blas ./configure --with[out]-(scalapack,lapack,blas) --with-blas=ibm_essl

15. How frequently do you refer to the LAPACK Users Guide?
Rarely

ScaLAPACK Usage

15. How frequently do you refer to the ScaLAPACK Users Guide?

Targeted Environment Specifics

Additional Information