> > > - I see some SIMD optimizations in arrow go binding, such as vectored > sum. [2] > > But arrow cpp lib doesn't leverage SIMD. [3] > > Why not optimize it in cpp lib so all languages can benefit? > You're welcome to contribute such optimizations to the C++ library
Note that even though C++ doesn't use explicit SIMD intrinsics often times the compiler will generate SIMD code because it can auto-vectorize the code. On Wed, Oct 30, 2019 at 7:25 AM Wes McKinney <wesmck...@gmail.com> wrote: > hi Yibo > > On Wed, Oct 30, 2019 at 2:16 AM Yibo Cai <yibo....@arm.com> wrote: > > > > Hi, > > > > I'm new to Arrow. Would like to seek for help about some questions. Any > comment is welcomed. > > > > - About source code tree, my understand is that "cpp" is the core arrow > libraries, "c_glib, go, python, ..." are language bindings to ease > integrating arrow into apps developed by that language. Is that correct? > > No. We have 6 core implementations: C++, C#, Go, Java, JavaScript, and Rust > > * C/GLib, MATLAB, Python, R bind to C++ > * Ruby binds to GLib > > > - Arrow implements many data types and aggregation functions(sum, mean, > ...). [1] > > IMO, more functions and types should be supported, like min/max, > vector/tensor operations, big number, etc. I'm not sure if this is in > arrow's scope, or the apps using arrow should deal with it themselves. > > Our objective at least in the C++ library is to have a generally > useful "standard library" that handles common application concerns. > Whether or not something is thought to be in scope may vary on a case > by case basis -- if you can't find a JIRA issue for something in > particular, please go ahead and open one. > > > - I see some SIMD optimizations in arrow go binding, such as vectored > sum. [2] > > But arrow cpp lib doesn't leverage SIMD. [3] > > Why not optimize it in cpp lib so all languages can benefit? > > You're welcome to contribute such optimizations to the C++ library > > > - Wes > > > [1] > https://github.com/apache/arrow/tree/master/cpp/src/arrow/compute/kernels > > [2] > https://github.com/apache/arrow/blob/master/go/arrow/math/float64_avx2_amd64.s > > [3] > https://github.com/apache/arrow/blob/master/cpp/src/arrow/compute/kernels/sum_internal.h#L99-L111 > > > > Yibo >
