CGAL users discussion list

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Dear all,

I am using CGAL::Convex_hull_d to compute the convex hull of a small set of
points in some n-dimensional space. Here, small means 2*n points, where n is
the number of dimensions of the space (3 <= n <= 6). Unfortunately, compute 
the
convex hull is the bottleneck of my implementation. Actually, the program
spends 87% of the time calling CGAL::Convex_hull_d.insert().

Today, my implementation takes several minutes to process simple data sets and
I want to make it run faster. My question is: There is some trick that I can
use to improve CGAL’s performance assuming a small number of input points? I
believe that the bottleneck inside CGAL is memory allocation.