Response #1: 2005-08-24

General

1. Is dense linear algebra a performance bottleneck in your applications?
No

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?
100s X 100s

4. Does your application come close to, or run out of memory on important problems?
Yes

5. Number of processors used for your application:

6. Which architectures do you use or intend to use in the next three years?
Sequential, Multi-core-thread, Distributed-memory

8. Please rank how the following features would be useful to your current or planned applications?

9. Do your applications solve linear algebra problems of the type?
Linear positive definite systems, General linear systems, Generalized eigenvalue, 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?
Vendor

6. Do your applications make direct LAPACK calls?
Yes

7. Do your applications use libraries which depend on LAPACK?
No

8. Do your applications use a higher-level interface to LAPACK?
No

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

11. From which languages do you call LAPACK routines?
C, Fortran 77

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

ScaLAPACK Usage

1. Do you use ScaLAPACK (or a vendor version of ScaLAPACK )?
No

2. If you do not use ScaLAPACK, why?
Not solving linear algebra

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

Targeted Environment Specifics

1. Under which operating system environments do your applications run?
Linux, Windows (other)

2. If your applications run in a shared-memory environment, which styles of parallelism do they employ?
Concurrent programs

3. If your applications run in a distributed-memory environment, which styles of parallelism do they employ?
Message passing

Additional Information