Den 13.02.2011 04:30, skrev Travis Oliphant:

One of the advantages of an open source community is that different needs get addressed by the people who need them. So, if you really need a faster sum and are willing to do the hard work to make it happen (or convince someone else to do it for you), then there will be many to say thank you when you are finished. You should know though that in my experience It is harder than you might think at first to "convince someone else to do it for you."

For things like sum (and may other ufuncs), one could just use Fortran instrincs and let the Fortran compiler do the rest. (Obviously NumPy should not depend on a Fortran compiler, unlike SciPy, but that is another matter.)

Assuming a wrapper takes care of C and Fortran ordering, we can just f2py this:

subroutine fortran_sum_1d( m, arr, out )
    use, intrinsic :: sum
    integer :: m
    real :: arr(m), out
    out = sum(arr)
end subroutine

subroutine fortran_sum_2d( m, n, arr, k, out, dim )
    use, intrinsic :: sum
    integer :: m, n, k, dim
    real :: arr(m,n), out(k)
    out = sum(arr, dim+1) ! fortran dims start at 1
end subroutine

Similar things can be done for other ufuncs. We can also use Fortran's "elemental" keyword to create our own. The Fortran compilers from Absoft and Intel (and possibly Portland) can even take code like this and make it efficient for multicore CPUs. (I don't know if GNU gfortran can do this too, but I don't expect it too.)

One limitation is that the Fortran compiler must know the number of dimensions, while NumPy arrays are flexible in this respect. Another limitation is strides, but we can deal with them if they are a multiple of the dtype size, but not arbitrary number of bytes like NumPy.

subroutine fortran_sum_1d_with_strides( m, s, arr, out )
    use, intrinsic :: sum
    integer :: m, s
    real, target :: arr(m)
    real, pointer, dimension(:) :: parr
    real :: out
    parr => arr(::s)
    out = sum(parr)
end subroutine

I think for most people, Fortran is much easier than using NumPy's C API. Creating fast "ufunc" like functions is very easy with Fortran 95.

If we e.g. want the L2 norm of a vector, it looks like this in Fortran:

subroutine l2norm( m, arr, out )
    use, intrinsic :: sum, sqrt
    integer :: m
    real :: arr(m), out
    out = sqrt(sum(arr**2)) ! looks quite like Python...
end subroutine

Just notice the messyness of C in comparison (there are much worse examples):

#include <Python.h>
#include <numpy/arrayobject.h//>
#include <math.h>

double l2norm(PyArrayObject *arr)
{
     double acc = 0.0, *y;
     char *addr = arr->data;
     for (int i=0; i<arr->dimensions[0]; i++) {
         y = (double *)addr;
         acc += y*y;
         addr +=  arr->strides[0];
     }
     return sqrt(acc);
}




Sturla










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