Hi Gyozo, If the arrays are small, then using arrow::compute::Sum might not give you huge performance improvement. IMO the advantage would be, the code base would be more organized.
IINM by default Sum benefits from SSE2 optimizations. But there are kernels implementations for AVX/AVX512 as well. But for these make real impact, you'd need a sizeable array. If the array size is small, it's possible that you'd be working within cache or even a single cache line. So I doubt vectorization would help there. Best On Thu, Mar 3, 2022, 05:30 Győző Gáspár <[email protected]> wrote: > Hi All, > > I am summing values like: > > #+BEGIN_SRC > scalar->value = scalar->value + array.Value(row); > #+END_SRC > > I plan to change this to use arrow compute API instead. The arrays I am > summing up are small, with ten or fewer items inside. > > My questions: > > - Can I expect arrow compute to be faster? > - Are there general guidelines? What is the minimal array size when the > compute API is faster than just summing values? > - Do I need specialized hardware to speed up arrow compute? > > -- > Győző Gáspár > Software Engineer > > Tenzir GmbH > Nagelsweg 41 > 20097 Hamburg > > https://tenzir.com > +49 40 209337260 > > Commercial Register Hamburg: HRB 148081 > VAT Number: DE314897407 > CEO: Matthias Vallentin, PhD >
