Broadword Implementation of Rank/Select Queries

Abstract

Research on succinct data structures (data structures occupying space close to the information-theoretical lower bound, but achieving speed similar to their standard counterparts) has steadily increased in the last few years. However, many theoretical constructions providing asymptotically optimal bounds are unusable in practise because of the very large constants involved. The study of practical implementations of the basic building blocks of such data structures is thus fundamental to obtain practical applications. In this paper we argue that 64-bit and wider architectures are particularly suited to very efficient implementations of rank (counting the number of ones up to a given position) and select (finding the position of the i-th bit set), two essential building blocks of all succinct data structures. Contrarily to typical 32-bit approaches, involving precomputed tables, we use pervasively broadword (a.k.a. SWAR—“SIMD in A Register”) programming, which compensates the constant burden associated to succinct structures by solving problems in parallel in a register. We provide an implementation named rank9 that addresses 2⁶⁴ bits, consumes less space and is significantly faster then current state-of-the-art 32-bit implementations, and a companion select9 structure that selects in nearly constant time using only access to aligned data. For sparsely populated arrays, we provide a simple broadword implementation of the Elias–Fano representation of monotone sequences. In doing so, we develop broadword algorithms for performing selection in a word or in a sequence of words that are of independent interest.