  Acceleration of algorithms is becoming a crucial problem, if larger data sets
are to be processed. Evaluation of algorithms is mostly done by using
computational geometry approach and evaluation of computational complexity.
However in todays engineering problems this approach does not respect that
number of processed items is always limited and a significant role plays also
speed of read/write operations. One general method how to speed up an algorithm
is application of space subdivision technique and usually the orthogonal space
subdivision is used. In this paper non-orthogonal subdivisions are described.
The proposed approach can significantly improve memory consumption and run-time
complexity. The proposed modified space subdivision techniques are demonstrated
on two simple problems Point-in-Convex Polygon and Point-in-Convex Polyhedron
tests.
