Antoine Pitrou wrote:
> By always using an aligned allocator there is some overhead:
> - all arrays occupy a bit more memory by a small average amount
> (probably 16 bytes average on a 64-bit machine, for a 16 byte
> guaranteed alignment)
NumPy arrays are Python objects. They have an overhea
Hello,
In https://github.com/numpy/numpy/issues/5312 there's a request for an
aligned allocator in Numpy (more than the default alignment of the
platform's memory allocator). The reason is that on modern
vectorization instruction sets, a certain alignment is required for
optimal performance (even
