How to vectorize with gcc? - Stack Overflow
Apr 4, 2020 · The v4 series of the gcc compiler can automatically vectorize loops using the SIMD processor on some modern CPUs, such as the AMD Athlon or Intel Pentium/Core chips. How …
python - Performance of Pandas apply vs np.vectorize to create …
Oct 6, 2018 · np.vectorize, list comprehension + zip and map methods, i.e. the top 3, all have roughly the same performance. This is because they use tuple and bypass some Pandas …
Is `-ftree-loop-vectorize` not enabled by `-O2` in GCC v12?
Dec 23, 2022 · SIMD, Vectorize. is enabled by -o2, loop unrolling makes the code much larger so it is a separate flag in -o2 and included in -o3. many times -o2 will out-perform -o3.
Using Numpy Vectorize on Functions that Return Vectors
Using Numpy Vectorize on Functions that Return Vectors Asked 15 years, 3 months ago Modified 2 years, 10 months ago Viewed 125k times
simd - What is "vectorization"? - Stack Overflow
Sep 14, 2009 · Many CPUs have "vector" or "SIMD" instruction sets which apply the same operation simultaneously to two, four, or more pieces of data. Modern x86 chips have the SSE …
How do I vectorize a function with Numba, when the function …
Jul 17, 2018 · I'd like to use Numba to vectorize a function that will evaluate each row of a matrix. This would essentially apply a Numpy ufunc to the matrix, as opposed to looping over the …
How to define a vectorized function in R - Stack Overflow
Sep 13, 2017 · As the title, I'd like to know how to define a vectorized function in R. Is it just by using a loop in the function? Is this method efficient? And what's the best practice ?
Comparing numba njit/vectorize/guvectorize - Stack Overflow
Dec 4, 2022 · I was expecting vectorize and guvectorize to be almost similar in speedup but while njit and guvectorize are almost equal to each other in time, vectorize is ~2 and ~10 times …
vectorization - vectorize.upstream_error - failed to parse upsert ...
Dec 12, 2024 · 1 I am trying to upsert a vector in my cloudflare vectorize index For now I am testing from my terminal using cURL Call I am making is this:
Most efficient way to map function over numpy array
Feb 5, 2016 · What is the most efficient way to map a function over a numpy array? I am currently doing: import numpy as np x = np.array ( [1, 2, 3, 4, 5]) # Obtain array of square ...