On Sun, Feb 7, 2016 at 4:39 PM, Nils Becker <nilsc.bec...@gmail.com> wrote: > Hi all, > > I wanted to know if there is any sane way to build numpy while linking to a > different implementation of libm? > A drop-in replacement for libm (e.g. openlibm) should in principle work, I > guess, but I did not manage to actually make it work. As far as I understand > the build code, setting MATHLIB=openlibm should suffice, but it did not. The > build works fine, but in the end when running numpy apparently the functions > of the system libm.so are used. I could not verify this directly (as I do > not know how) but noticed that there is no performance difference between > the builds - while there is one with pure C programs linked against libm and > openlibm. > Using amdlibm would require some work as the functions are prefixed with > "_amd", I guess? Using intels libimf should work when using intels compiler, > but I did not try this. With gcc I did not get it to work. > > A quite general question: At the moment the performance and the accuracy of > the base mathematical functions depends on the platform and > libm-Implementation of the system. Although there are functions defined in > npy_math, they are only used as fall-backs, if they are not provided by a > library. (correct me if I am wrong here) > Is there some plan to change this in the future and provide defined > behaviour (specified accuracy and/or speed) across platforms? As I > understood it Julia started openlibm for this reason (which is based on > fdlibm/msun, same as npy_math).
The npy_math functions are used if otherwise unavailable OR if someone has at some point noticed that say glibc 2.4-2.10 has a bad quality tan (or whatever) and added a special case hack that checks for those particular library versions and uses our built-in version instead. It's not the most convenient setup to maintain, so there's been some discussion of trying openlibm instead [1], but AFAIK you're the first person to find the time to actually sit down and try doing it :-). You should be able to tell what math library you're linked to by running ldd (on linux) or otool (on OS X) against the .so / .dylib files inside your built copy of numpy -- e.g. ldd numpy/core/umath.cpython-34m.so (exact filename and command will vary depending on python version and platform). -n [1] https://github.com/numpy/numpy/search?q=openlibm&type=Issues&utf8=%E2%9C%93 -- Nathaniel J. Smith -- https://vorpus.org _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
