Re: ANN: LAPACK and ScaLAPACK new functionality survey

[Paul Kienzle]

The only candidates that leap to mind are matrix sqrt, exp and log for 
which
there are accurate algorithms which are not built upon diagonalization.
There are also candidates in control systems, such as the discrete 
Lyapunov
solver  (a x a' - x + b = 0), which has a loop, but I don't know how 
broadly
useful it is.  Anyone care to put forward an argument for any of these?

I'm assuming that sparse methods are beyond the scope of LAPACK.
And fft, filtering, convolution, optimization, special functions, 
sorting,
random number generation, quadrature, interpolation, ...

Paul Kienzle
address@hidden

On Jun 1, 2004, at 5:30 PM, Jason Riedy wrote:

> [mailed jointly to address@hidden, address@hidden
> to reach users with relevant experience.  watch where your replies
> go.  what would make using LAPACK and ScaLAPACK easier for Octave
> and R developers?  -- ejr, not subscribed]
>
> We plan to update the LAPACK and ScaLAPACK libraries and would like to 
> have
> feedback from users on what functionalities they think are missing and 
> would
> be needed in order to make these libraries more useful for the 
> community. We
> invite you to enter your suggestions in the form below. It would be 
> most
> useful to have input by June 16th, although we would welcome your 
> input at
> any time.
>
> Both LAPACK and ScaLAPACK provide well-tested, open source, reviewed 
> code
> implementing trusted algorithms that guarantee reliability, efficiency 
> and
> accuracy. Any new functionality must adhere to these standards and 
> should
> have a significant impact in order to justify the development costs. 
> We are
> also interested in suggestions regarding user interfaces, 
> documentation,
> language interfaces, target (parallel) architectures and other issues, 
> again
> provided the impact is large enough.
>
> We already plan to include a variety of improved algorithms discovered 
> over
> the years by a number of researchers (e.g. faster or more accurate
> eigenvalue and SVD algorithms, extra precise iterative refinement, 
> recursive
> blocking for some linear solvers, etc.). We also know of a variety of 
> other
> possible functions we could add (e.g. updating and downdating
> factorizations), but are uncertain of their impact.
>
> Please see http://icl.cs.utk.edu/lapack-survey.html for the survey.
> We would like to have your input by June 16th, 2004.
>
> Regards,
> Jack Dongarra, Jim Demmel, and Sven Hammarling