On 16.01.2017 20:28, Gregory P. Smith wrote:
Is there a good reason not to detect single expression multiply adds
and just emit a new FMA bytecode?
Same question here.
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On 16/01/17 18:29, Mathieu TORTUYAUX wrote:
Thank you everyone for those feedbacks !
So I made a Django version to check if dependencies are up-to-date, using
pip lib and get_outdated method. :)
Mathieu, please do not attach images to posts to this list/newsgroup.
It is text-only, and some of
Is there a good reason not to detect single expression multiply adds and
just emit a new FMA bytecode?
Is our goal for floats to strictly match the result of the same operations
coded in unoptimized C using doubles?
Or can we be more precise on occasion?
I guess a similar question may be asked o
My understanding is that NumPy does NOT currently support a direct FMA
operation "natively." However, higher-level routines like
`numpy.linalg.solve` that are linked to MKL or BLAS DO take advantage of
FMA within the underlying libraries.
On Mon, Jan 16, 2017 at 10:06 AM, Guido van Rossum
wrote:
Thank you everyone for those feedbacks !
So I made a Django version to check if dependencies are up-to-date, using
pip lib and get_outdated method. :)
Le dimanche 15 janvier 2017 00:25:26 UTC-5, Mathieu TORTUYAUX a écrit :
>
> Hello everyone,
>
> I'm used to work with python and contribute to
Does numpy support this?
--Guido (mobile)
On Jan 16, 2017 7:27 AM, "Stephan Houben" wrote:
> Hi Steve,
>
> Very good!
> Here is a version which also handles the nan's, infinities,
> negative zeros properly.
>
> ===
> import math
> from fractions import Fraction
>
> def fma2(x, y, z)
Hi Steve,
Very good!
Here is a version which also handles the nan's, infinities,
negative zeros properly.
===
import math
from fractions import Fraction
def fma2(x, y, z):
if math.isfinite(x) and math.isfinite(y) and math.isfinite(z):
result = float(Fraction(x)*Fraction(y
On Mon, Jan 16, 2017 at 11:01:23AM +0100, Stephan Houben wrote:
[...]
> So the following would not be a valid FMA fallback
>
> double bad_fma(double x, double y, double z) {
> return x*y + z;
> }
[...]
> Upshot: if we want to provide a software fallback in the Python code, we
> need to do somet
Hi Victor,
The fallback implementations in the various libc take care
to preserve the correct rounding behaviour.
Let me stress that *fused* multiply-add means the specific rounding
behaviour as defined in the standard IEEE-754 2008
(i.e. with guaranteed *no* intermediate rounding).
So the follo
2017-01-15 18:25 GMT+01:00 Juraj Sukop :
> C99 includes `fma` function to `math.h` [6] and emulates the calculation if
> the FMA instruction is not present on the host CPU [7].
If even the libc function has a fallback on x*y followed by +z, it's
fine to add such function to the Python stdlib. It m
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