On Wed, Jan 19, 2022 at 11:50 AM Francesc Alted <faltet@gmail.com> wrote:
On Wed, Jan 19, 2022 at 7:33 AM Stefan van der Walt <stefanv@berkeley.edu> wrote:
On Tue, Jan 18, 2022, at 21:55, Warren Weckesser wrote:
expr = 'z.real**2 + z.imag**2'
z = generate_sample(n, rng)
🤔 If I duplicate the `z = ...` line, I get the fast result throughout. If, however, I use `generate_sample(1, rng)` (or any other value than `n`), it does not improve matters.
Could this be a memory caching issue?
I can also reproduce that, but only on my Linux boxes. My MacMini does not notice the difference.
Interestingly enough, you don't even need an additional call to `generate_sample(n, rng)`. If one use `z = np.empty(...)` and then do an assignment, like:
z = np.empty(n, dtype=np.complex128) z[:] = generate_sample(n, rng)
then everything runs at the same speed:
Just turning the view into a copy inside `generate_sample()` will also make the difference go away, for probably the same reason as this version. András
numpy version 1.20.3
142.3667 microseconds 142.3717 microseconds 142.3781 microseconds
142.7593 microseconds 142.3579 microseconds 142.3231 microseconds
As another data point, by doing the same operation but using numexpr I am not seeing any difference either, not even on Linux:
numpy version 1.20.3 numexpr version 2.8.1
95.6513 microseconds 88.1804 microseconds 97.1322 microseconds
105.0833 microseconds 100.5555 microseconds 100.5654 microseconds
[it is rather like a bit the other way around, the second iteration seems a hair faster] See the numexpr script below.
I am totally puzzled here.
""" import timeit import numpy as np import numexpr as ne
def generate_sample(n, rng): return rng.normal(scale=1000, size=2*n).view(np.complex128)
print(f'numpy version {np.__version__}') print(f'numexpr version {ne.__version__}') print()
rng = np.random.default_rng() n = 250000 timeit_reps = 10000
expr = 'ne.evaluate("zreal**2 + zimag**2")'
z = generate_sample(n, rng) zreal = z.real zimag = z.imag for _ in range(3): t = timeit.timeit(expr, globals=globals(), number=timeit_reps) print(f"{1e6*t/timeit_reps:9.4f} microseconds") print()
z = generate_sample(n, rng) zreal = z.real zimag = z.imag for _ in range(3): t = timeit.timeit(expr, globals=globals(), number=timeit_reps) print(f"{1e6*t/timeit_reps:9.4f} microseconds") print() """
-- Francesc Alted _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-leave@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: deak.andris@gmail.com