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Tiny Pointers

  • Michael A. Bender
  • , Alex Conway
  • , Martín Farach-Colton
  • , William Kuszmaul
  • , Guido Tagliavini
  • VMware Research Group
  • Rutgers University
  • Massachusetts Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

This paper introduces a new data-structural object that we call the tiny pointer. In many applications, traditional log n-bit pointers can be replaced with o(log n)-bit tiny pointers at the cost of only a constant-factor time overhead and a small probability of failure. We develop a comprehensive theory of tiny pointers, and give optimal constructions for both fixed-size tiny pointers (i.e., settings in which all of the tiny pointers must be the same size) and variable-size tiny pointers (i.e., settings in which the average tiny-pointer size must be small, but some tiny pointers can be larger). If a tiny pointer references an element in an array filled to load factor 1 - δ, then the optimal tiny-pointer size is Θ(log log log n + log δ-1) bits in the fixed-size case, and Θ(log δ-1) expected bits in the variable-size case. Our tiny-pointer constructions also require us to revisit several classic problems having to do with balls and bins; these results may be of independent interest. Using tiny pointers, we revisit five classic data-structure problems. We show that: • A data structure storing n v-bit values for n keys with constant-time modifications/queries can be implemented to take space nv + O(n log(r) n) bits, for any constant r > 0, as long as the user stores a tiny pointer of expected size O(1) with each key-here, log(r) n is the r-th iterated logarithm. • Any binary search tree can be made succinct with constant-factor time overhead, and can even be made to be within O(n) bits of optimal if we allow for O(log n)-time modifications-this holds even for rotation-based trees such as the splay tree and the red-black tree. • Any fixed-capacity key-value dictionary can be made stable (i.e., items do not move once inserted) with constant-time overhead and 1 + o(1) space overhead. • Any key-value dictionary that requires uniform-size values can be made to support arbitrary-size values with constant-time overhead and with an additional space consumption of log(r) n + O(log j) bits per j-bit value for an arbitrary constant r > 0 of our choice. • Given an external-memory array A of size (1 + ε)n containing a dynamic set of up to n key-value pairs, it is possible to maintain an internal-memory stash of size O(n log ε-1) bits so that the location of any key-value pair in A can be computed in constant time (and with no IOs). These are all well studied and classic problems, and in each case tiny pointers allow for us to take a natural space-inefficient solution that uses pointers and make it space-efficient for free.

Original languageEnglish
Title of host publication34th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2023
PublisherAssociation for Computing Machinery
Pages477-508
Number of pages32
ISBN (Electronic)9781611977554
StatePublished - 2023
Event34th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2023 - Florence, Italy
Duration: Jan 22 2023Jan 25 2023

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
Volume2023-January

Conference

Conference34th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2023
Country/TerritoryItaly
CityFlorence
Period01/22/2301/25/23

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