> This could change in the future to be more general purpose.  For example,
> hardware-based computations using quaternions and octonions.  As far as I am
> aware, it isn't done today for purely mathematical reasons; no one knows
> how.  And as far as I'm aware, such a mathematical breakthrough would be
> huge, but not something graphics vendors would pursue/fund, since it is
> "basic research" that can't be patented and so all graphics processors would
> get the same speedup. [1]


Incidentally, this research has been going on for at least 10 years
already and has made significant progress in terms of compiler tools
and software systems that can be used for real-time systems.  In
Guadalajara, there's a robotics group led by Eduardo
Bayro-Corrochano[1] that makes amazing machines that perform their
computations in an intrinsically spatial manner using geometric
(Clifford) algebra.  One of the issues with this algebra is that the
dimensionality of the computational space grows combinatorially.  The
standard 3D conformal model (5D Minkowski space) is a 32 dimensional
multi-vector.  Fortunately, there's some really good software that
optimizes away the many redundancies and zero-ops called Gaigen[2],
which can handle up to 12D Clifford Algebras.  Geometric algebra
subsumes quaternions and adds a lot more interesting structures and
operations.

I don't think it requires basic research since it's just linear
algebra and easily maps to GPU hardware.  Plus the research has
already been done.  The software already exists for use if you want
it.  I'm really not sure what interest the manufacturers would have in
it though since their more specific applications than the general case
of GA lends itself to more optimization.  Also, there's an entire
world of mathematics that would have to be taught to everyone since
you aren't going to find courses in CS departments on this stuff
except in a handful of labs around the world (Netherlands, Saudia
Arabia, Mexico, Cambridge (in physics department) ...)


Here are some papers about GA and hardware:

using FPGAs: 
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.159.1691&rep=rep1&type=pdf
conformal collision detection on GPUs:
http://eduardoroa.3dsquash.com/portafolioeduv2/document/publications/SIACG_article.pdf

and there are others implementing generic GA ops in graphics hardware
that I wasn't able to find as quickly.


[1] http://www.gdl.cinvestav.mx/edb/
[2] http://staff.science.uva.nl/~fontijne/g25.html

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