vector-qsort

Vectorized quicksort for NumPy arrays using Google Highway SIMD.

pip install vector-qsort

Quick start

import numpy as np
import vector_qsort

data = np.array([3.14, -1.5, 42.0, 0.0, -100.5, 2.71], dtype=np.float32)

# In-place SIMD sort
vector_qsort.sort(data)
# array([-100.5, -1.5, 0.0, 2.71, 3.14, 42.0], dtype=float32)

# Descending
vector_qsort.sort(data, desc=True)

# Non-mutating copy
sorted_data = vector_qsort.sorted(data)

sort() sorts 1D contiguous arrays in place with zero copies. sorted() returns a sorted copy. Supports float32, float64, int32, uint32, int64, uint64, int16, and uint16.

Benchmarks

Measured on Apple Silicon (ARM NEON) vs NumPy's native in-place np.sort():

python bench/bench_sort.py

Note on scalar sorts

Modern scalar sorts like driftsort and ipnsort excel at generic types and presorted run-detection. vector-qsort is designed specifically for raw numeric throughput on contiguous buffers by saturating SIMD vector lanes.

License

MIT © Hemanth.HM