Optimal Sorting Circuits for Short Keys

TL;DR

This paper presents a new sorting circuit that is both size-efficient and has logarithmic depth, improving upon previous work by achieving optimal size and depth simultaneously for short keys.

Contribution

The authors construct a sorting circuit with optimal size and depth for short keys, closing the gap left by prior work that sacrificed depth for size.

Findings

Achieves size $O(n) imes ext{min}(k, ext{log} n)$ for sorting circuits.

Constructs a sorting circuit with depth $O( ext{log} n)$.

Generalizes the AKS sorting circuit with improvements in size for short keys.

Abstract

A long-standing open question in the algorithms and complexity literature is whether there exist sorting circuits of size $o(n \log n)$. A recent work by Asharov, Lin, and Shi (SODA'21) showed that if the elements to be sorted have short keys whose length $k = o(\log n)$, then one can indeed overcome the $n\log n$ barrier for sorting circuits, by leveraging non-comparison-based techniques. More specifically, Asharov et al.~showed that there exist $O(n) \cdot \min(k, \log n)$-sized sorting circuits for $k$-bit keys, ignoring $poly\log^*$ factors. Interestingly, the recent works by Farhadi et al. (STOC'19) and Asharov et al. (SODA'21) also showed that the above result is essentially optimal for every key length $k$, assuming that the famous Li-Li network coding conjecture holds. Note also that proving any {\it unconditional} super-linear circuit lower bound for a wide class of problems is beyond the reach of current techniques. Unfortunately, the approach taken by Asharov et al.~to achieve optimality in size somewhat crucially relies on sacrificing the depth: specifically, their circuit is super-{\it poly}logarithmic in depth even for 1-bit keys. Asharov et al.~phrase it as an open question how to achieve optimality both in size and depth. In this paper, we close this important gap in our understanding. We construct a sorting circuit of size $O(n) \cdot \min(k, \log n)$ (ignoring $poly\log^*$ terms) and depth $O(\log n)$. To achieve this, our approach departs significantly from the prior works. Our result can be viewed as a generalization of the landmark result by Ajtai, Koml\'os, and Szemer\'edi (STOC'83), simultaneously in terms of size and depth. Specifically, for $k = o(\log n)$, we achieve asymptotical improvements in size over the AKS sorting circuit, while preserving optimality in depth.