Hi Sturla, > The proper way to speed up "dot(a*b+c*sqrt(d), e)" is to get rid of > temporary intermediates. I implemented a patch http://projects.scipy.org/numpy/ticket/1153 that reduces the number of temporary intermediates. In your example from 4 to 2. There is a big improvement in terms of memory footprint, and some improvement in terms of speed (especially for large matrices) but not as much as I expected.
In your example > result = 0 > for i in range(n): > result += (a[i]*b[i] + c[i]*sqrt(d[i])) * e[i] another big speedup could come from the fact that it makes better use of the cache. That is exactly why numexpr is faster in these cases. I hope one day numpy will be able to perform such optimizations. Best, Luca _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
