x86-simd-sort

C++ template library for high performance SIMD based sorting routines for 16-bit, 32-bit and 64-bit data types. The sorting routines are accelerated using AVX-512/AVX2 when available. The library auto picks the best version depending on the processor it is run on. If you are looking for the AVX-512 or AVX2 specific implementations, please see README file under src/ directory. The following routines are currently supported:

Sort routines on arrays

x86simdsort::qsort(T* arr, size_t size, bool hasnan);
x86simdsort::qselect(T* arr, size_t k, size_t size, bool hasnan);
x86simdsort::partial_qsort(T* arr, size_t k, size_t size, bool hasnan);

Supported datatypes: T $\in$ [_Float16, uint16_t, int16_t, float, uint32_t, int32_t, double, uint64_t, int64_t]

Key-value sort routines on pairs of arrays

x86simdsort::keyvalue_qsort(T1* key, T2* val, size_t size, bool hasnan);

Supported datatypes: T1, T2 $\in$ [float, uint32_t, int32_t, double, uint64_t, int64_t] Note that keyvalue sort is not yet supported for 16-bit data types.

Arg sort routines on arrays

std::vector<size_t> arg = x86simdsort::argsort(T* arr, size_t size, bool hasnan);
std::vector<size_t> arg = x86simdsort::argselect(T* arr, size_t k, size_t size, bool hasnan);

Supported datatypes: T $\in$ [_Float16, uint16_t, int16_t, float, uint32_t, int32_t, double, uint64_t, int64_t]

Build/Install

meson is the used build system. Command to build and install the library:

meson setup --buildtype release builddir && cd builddir
meson compile
sudo meson install

Once installed, you can use pkg-config --cflags --libs x86simdsortcpp to populate the right cflags and ldflags to compile and link your C++ program. This repository also contains a test suite and benchmarking suite which are written using googletest and google benchmark frameworks respectively. You can configure meson to build them both by using -Dbuild_tests=true and -Dbuild_benchmarks=true.

Example usage

#include "x86simdsort.h"

int main() {
    std::vector<float> arr{1000};
    x86simdsort::qsort(arr, 1000, true);
    return 0;
}

Details

x86simdsort::qsort is equivalent to qsort in C or std::sort in C++.
x86simdsort::qselect is equivalent to std::nth_element in C++ or np.partition in NumPy.
x86simdsort::partial_qsort is equivalent to std::partial_sort in C++.
x86simdsort::argsort is equivalent to np.argsort in NumPy.
x86simdsort::argselect is equivalent to np.argpartition in NumPy.

Supported datatypes: uint16_t, int16_t, _Float16, uint32_t, int32_t, float, uint64_t, int64_t, double. Note that _Float16 will require building this library with g++ >= 12.x. All the functions have an optional argument bool hasnan set to false by default (these are relevant to floating point data types only). If your array has NAN's, the the behaviour of the sorting routine is undefined. If hasnan is set to true, NAN's are always sorted to the end of the array. In addition to that, qsort will replace all your NAN's with std::numeric_limits<T>::quiet_NaN. The original bit-exact NaNs in the input are not preserved. Also note that the arg methods (argsort and argselect) will not use the SIMD based algorithms if they detect NAN's in the array. You can read details of all the implementations here.

Downstream projects using x86-simd-sort

NumPy uses this as a submodule to accelerate np.sort, np.argsort, np.partition and np.argpartition.
A slightly modifed version this library has been integrated into openJDK.
GRAPE: C++ library for parallel graph processing.
AVX-512 version of the key-value sort has been submitted to Oceanbase.

jerrycxj/x86-simd-sort