Hi Aldrin, Use Case: I am taking a subset of a really large input_array. It is used in places where OpenMP-like and MPI-like parallelism are used. So vectorization seems to be the next low-hanging fruit.
I have added this to the original stackoverflow post. On Thu, Jun 23, 2022 at 5:53 PM Aldrin <akmon...@ucsc.edu.invalid> wrote: > Without knowing implementation details of the Take function, I know that > Arrow uses xsimd and does try to enable the compiler to vectorize code > where it can. To clarify, are you asking how to improve the performance > you're seeing, or are you asking how to check if the compiled code is using > vector instructions? I think a little bit more context about what you know > and what you're trying to do could also help others who know more about > this function (and vectorization in Arrow in general) to chime in. > > Aldrin Montana > Computer Science PhD Student > UC Santa Cruz > > > On Thu, Jun 23, 2022 at 12:41 PM Chak-Pong Chung <chakpongch...@gmail.com> > wrote: > > > correction: not clang, I meant the Vectorizers from LLVM > > > > https://llvm.org/docs/Vectorizers.html > > > > if we can use it with arrow array > > > > On Thu, Jun 23, 2022 at 3:35 PM Chak-Pong Chung <chakpongch...@gmail.com > > > > wrote: > > > > > I asked a question here about vectorized processing. > > > > > > > > > > > > https://stackoverflow.com/questions/72735678/how-to-vectorize-arrowcomputetake > > > > > > Any idea? I am also open to the approaches like Intel MKL, xsimd, clang > > > and so on. > > > > > > > > > > > > -- > > > Regards, > > > Chak-Pong > > > > > > > > > -- > > Regards, > > Chak-Pong > > > -- Regards, Chak-Pong
