I remember a conversation in 1994 I had with Lennart Johnsson who led the
development of the math libraries for the Thinking Machines (which were way
ahead of their time). He recounted being told by various academic types that
they would not be purchasing Thinking Machines but instead IBM Sps and Intel
paragons because those other machines had no math libraries thus there was
plenty of "research" the academic types could do on them that would be
redundant (and hence unpublishable) on the Thinking Machines.
So what you do depends on your research plans.
1) If you are in a scientific area (materials, engineering, ?. whatever) then
you should use PETSc to do NEW simulations that other people have not done yet
(and cannot do) with new or more detailed models etc. For example, if everyone
in your community drops some "stuff" from their model because they "are too
hard" to include you can include them in the model and then demonstrate they
are important. Don't just run the standard models people have been running for
decades do models that other people can only dream about.
2) If you are in mathematics/CS numerical analysis then you need to do
innovative things that combine several capabilities in new ways.
Barry
On Nov 9, 2012, at 9:28 AM, w_ang_temp <w_ang_temp at 163.com> wrote:
> By the way, as a graduate student, I find that it is difficult to write a
> paper just using PETSc
> to deal with a large problem. Because it seems that there is no an innovative
> idea by just using
> the available things. It is also not easy to get something new based on the
> src of PETSc.
> Any suggestions?
> Thanks.
> Jim
>
>
