Dear Tim,
Many thanks - this was illuminating and helped me understand the
bottleneck. But it seems I did not give the correct amount of information
in my question. In fact, I also want to access A[ idx ] for general index
vectors idx that do not necessarily belong to the L array. For example, I
may be given a set of vectors in an array R, d x K and want to access
A[ L[:, n] + R[:, m] ],
then loop over n, m and do some calculations.
These sort of calculations are at the core of the code and I want the
syntax as simple and intuitive as possible to avoid making mistakes.
Can I confirm something: is it true that when I do
A[ L[:, Lcol] ]
then L[:, Lcol] creates a new d-dimensional array and copies that data into
that array? Can this at all be avoided? (I believe this is the bottlenbeck
in what I do?)
I've now tried this again in the form
module damod
export darray3
immutable darray3
data
end
export getindex
getindex(a::darray3, idx) = a.data[idx[1], idx[2],idx[3]]
end
This makes only a small difference.
elapsed time: 0.163860853 seconds (104000080 bytes allocated, 28.46% gc time)
vs some variant of your code:
elapsed time: 0.003819349 seconds (96 bytes allocated)
What strikes me as odd here is that *104,000,080 bytes* are being allocated. If
L is an Int16 array, then it should be no more than 100^3 x 3 x 8 = 6,000,000 ?
Any further thoughts will be much appreciated.
Christoph
