Hi Armin,
> Do you mind if I merge this branch 'float-ops' into the
> standard repo?
I'm totally fine with a merge.
Best regards,
Toni
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19:08 schrieb Armin Rigo:
> Hi Toni,
>
> On 6 November 2014 18:29, Toni Mattis
> wrote:
>> thanks for the advice. I tried what Armin proposed and like to share my
>> results with you:
>>
>> https://bitbucket.org/amintos/pypy/commits/937254cbc554adfb748e3b5eeb44b
Hi all,
thanks for the advice. I tried what Armin proposed and like to share my
results with you:
https://bitbucket.org/amintos/pypy/commits/937254cbc554adfb748e3b5eeb44bf765d204b9d?at=default
Keeping in mind what Steve and Maciej pointed out, I restricted the
optimization to floats that are "no
Hello,
I discovered that PyPy's JIT generates "DIVSD" instructions on xmm
registers when dividing a float by a constant C. This consumes an order
of magnitude more CPU cycles than the corresponding "MULSD" instruction
with a precomputed 1/C.
I know that only powers of two have an exact reciprocal
Hi,
I'm trying to figure out the fastest way in PyPy to introduce
abstractions into loops, e.g. refactoring the following code:
def sum_direct(data):
s = 0
for i in data:
if i < 5:
s += i + 1
return s
to something like:
def sum_lambda(data):
filter_func =
