[Numpy-discussion] powerpc yellow dog linux port of numpy
Fri Apr 18 20:35:39 CDT 2008
On Fri, Apr 18, 2008 at 8:19 PM, Vincent Broman <email@example.com> wrote:
> I reported back on August 30 to this list,
> with some discussion following on September 4 and 5,
> about my attempt to build numpy on an ancient powerpc setup.
> I'm running yellow dog linux 2.1, gcc 184.108.40.20610111, on processors from Curtiss-Wright Controls.
> Don't tell me to just upgrade; this configuration will be
> fighting the good fight for several more years.
> I just retried with the latest numpy (svn yesterday) and gotten further than I did before.
> umathmodule.c gets many compiler errors from gcc, of two kinds.
> The simpler were like
> warning: conflicting types for built-in function `sinl'
> repeated for `cosl', `fabsl', and `sqrtl'.
> These seem to be caused by npy_longdouble being typedef'ed as double not long double,
> due to the latter two types having the same size.
> umathmodule.c defines its own sinl, sqrtl, etc. with npy_longdouble arguments and results,
> which then conflict with the builtin sinl, sqrtl provided by gcc that expect long double.
We check for the presence of expl() to determine if all of the rest
are provided and set the HAVE_LONGDOUBLE_FUNCS flag. It is possible
that you don't have expl() but do have these other functions.
> I worked around that by adding the "-fno-builtin" argument to the extra_compiler_args in setup.py.
This is not unreasonable.
> The other compiler complaints from the same file were:
> inconsistent operand constraints in an `asm'
> which came from every line that raised a division by zero exception,
> the code in each case being "feraiseexcept( FE_DIVBYZERO)" after preprocessing.
> That function is defined in fenv.h with a "__THROW" attribute,
> but I saw no sign of it being an inline asm or anything.
> I don't understand "__THROW".
> I'm afraid I would need to find the asm code involved, before I could
> see what "operand constraints" are "inconsistent".
> Any hints where to look?
> Any way to make the call go to a nice simple library instead?
In the file numpy/core/include/numpy/ufuncobject.h, there is a stanza
that looks like this:
#if defined(__GLIBC__) || defined(__APPLE__) || defined(__MINGW32__)
I assume that you have __GLIBC__ defined. You will have to find your
platform's fenv.[ch] file from your libc sources. You may want to
comment out all of that and use our included
Also, edit numpy/core/setup.py to include these files for your
platform in addition to Cygwin.
# Don't install fenv unless we need them.
if sys.platform == 'cygwin':
"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
-- Umberto Eco
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