On 23.12.20 14:42, PIERRE AUGIER wrote:
I wrote another very simple benchmark that should not depend on
auto-vectorization. The bench function is:
```python
def sum_x(positions):
result = 0.0
for i in range(len(positions)):
result += positions[i].x
return result
```
Th
I think I understood that what is very slow compared to Julia is looping over a
list of Python objects.
def loop_over_list_of_objects(l):
for o in l:
o
loop_over_list_of_objects([object() for _ in range(1000)])
See https://github.com/paugier/nbabel/blob/master/py/microbench_sum_x.py
- Mail original -
> De: "David Edelsohn"
> À: "PIERRE AUGIER"
> Cc: "pypy-dev"
> Envoyé: Lundi 21 Décembre 2020 23:47:22
> Objet: Re: [pypy-dev] Differences performance Julia / PyPy on very similar
> codes
> You did not state on exactly what system you are conducting the
> experiment,
