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Many of the matrices found in the Matrix Market were obtained by running
application codes which generated them. In many cases these codes are
parameterized so that a wide range of matrices could actually be produced.
A trivial example might be a code that generates a discrete 3D Laplacian
for any set of grid sizes. Such a code could be used to generate matrices
with the same general structure, but of any order. In other cases matrices
with differing numerical properties could be obtained by varying various
parameters, such the Reynolds number in a fluids computation. Such codes
are available with the SPARSKIT distribution, for example.
A service like Matrix Market could provide access to such codes in a variety
of ways.
- Downloading Source Code.
If freely available, the source code of a matrix generator itself
could be simply made available for downloading. This would be useful
for embedding the generator within a larger code for which tested
sparse linear algebra software over a range of parameters presented
by the generator.
- Remote Execution Service.
If a user were only interested in a few particular instances of the
parameter set, then having the ability run the generator remotely
would be useful. In that case, an HTML form would be presented to
specify the parameters of interest; submitting the form would cause
the generator to run at the Matrix Market site, after which the
generated matrix would be returned to the user.
Such a service could also be used to provide access to proprietary
matrix generators (with permission of the authors, of course).
- Executable WWW Content.
A third option is to provide the matrix generator as executable WWW
content such as provided by Java (Flanagan,
1996). In this case, the generator is
downloaded to the user's WWW browser, where it queries the user for
values of its parameters, and then executes on the user's local machine.
This is a more scalable approach than providing a remote execution
service, but will present some challenges in that there has yet been
little experience in developing portable, reliable and efficient
floating-point applications in this environment.
Next: Dense Matrices
Up: Extensions
Previous: Additional Numerical Indicators
Jack Dongarra
Thu May 30 12:55:31 EDT 1996