Vectorized and performance-portable Quicksort

Recent works showed that implementations of Quicksort using
vector CPU instructions can outperform the non-vectorized algorithms in
widespread use. However, these implementations are typically single-threaded,
implemented for a particular instruction set, and restricted to a small set of
key types. We lift these three restrictions: our proposed vqsort
algorithm integrates into the state-of-the-art parallel sorter ips4o,
speeding it up by a factor of 1.5 to 1.8. The same implementation works on seven
instruction sets (including SVE and RISC-V V) across four platforms. It also
supports floating-point and 16-128 bit integer keys. To the best of our
knowledge, this is the fastest sort for non-tuple keys on CPUs, up to 20 times
as fast as the sorting algorithms implemented in standard libraries. This paper
focuses on the practical engineering aspects enabling the speed and portability,
which we have not yet seen demonstrated for a Quicksort implementation.
Furthermore, we introduce compact and transpose-free sorting networks for
in-register sorting of small arrays, and a vector-friendly pivot sampling
strategy that is robust against adversarial input.

• Algorithms and Theory

• Hardware and Architecture