[Numpy-discussion] OT: performance in C extension; OpenMP, or SSE ?
Tue Feb 15 09:54:55 CST 2011
My first move would be to add a restrict keyword to dist (i.e. dist is the
only pointer to the specific memory location), and then declare dist_ inside
the first loop also with a restrict.
Then, I would run valgrind or a PAPI profil on your code to see what causes
the issue (false sharing, ...)
2011/2/15 Sebastian Haase <firstname.lastname@example.org>
> I assume that someone here could maybe help me, and I'm hoping it's
> not too much off topic.
> I have 2 arrays of 2d point coordinates and would like to calculate
> all pairwise distances as fast as possible.
> Going from Python/Numpy to a (Swigged) C extension already gave me a
> 55x speedup.
> (.9ms vs. 50ms for arrays of length 329 and 340).
> I'm using gcc on Linux.
> Now I'm wondering if I could go even faster !?
> My hope that the compiler might automagically do some SSE2
> optimization got disappointed.
> Since I have a 4 core CPU I thought OpenMP might be an option;
> I never used that, and after some playing around I managed to get
> (only) 50% slowdown(!) :-(
> My code in short is this:
> (My SWIG typemaps use obj_to_array_no_conversion() from numpy.i)
> -------<Ccode> ----------
> void dists2d(
> double *a_ps, int nx1, int na,
> double *b_ps, int nx2, int nb,
> double *dist, int nx3, int ny3) throw (char*)
> if(nx1 != 2) throw (char*) "a must be of shape (n,2)";
> if(nx2 != 2) throw (char*) "b must be of shape (n,2)";
> if(nx3 != nb || ny3 != na) throw (char*) "c must be of shape (na,nb)";
> double *dist_;
> int i, j;
> #pragma omp parallel private(dist_, j, i)
> #pragma omp for nowait
> //num_threads=omp_get_num_threads(); --> 4
> dist_ = dist+i*nb; // dists_ is only
> introduced for OpenMP
> *dist_++ = sqrt( sq(a_ps[i*nx1] - b_ps[j*nx2]) +
> sq(a_ps[i*nx1+1] -
> b_ps[j*nx2+1]) );
> -------</Ccode> ----------
> There is probably a simple mistake in this code - as I said I never
> used OpenMP before.
> It should be not too difficult to use OpenMP correctly here
> or - maybe better -
> is there a simple SSE(2,3,4) version that might be even better than
> OpenMP... !?
> I supposed, that I did not get the #pragma omp lines right - any idea ?
> Or is it in general not possible to speed this kind of code up using OpenMP
> Sebastian Haase
> NumPy-Discussion mailing list
Information System Engineer, Ph.D.
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