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static_maps: consteval std::map and std::unordered_map Implementations in C++23

Isaac D. Myhal, Oliver Serang

TL;DR

Using consteval from C++23, this library implements efficient, new versions of std::map and std::unordered_map for use when the keys are known at compile time, making this library the overall fastest drop-in hashing alternative to std::unordered_map.

Abstract

Using consteval from C++23, we implement efficient, new versions of std::map and std::unordered_map for use when the keys are known at compile time. We demonstrate superior performance of our unordered_map on three demonstration use-cases: Lookup of elemental mass from atomic symbol, lookup of amino acid from codon, and modification of stock prices from S&P 500 ticker symbols all produced runtimes <40%, <35%, <73% of the respective runtimes of the std implementations. Our library runimes were <80%, <45%, <97% of the lookup time of Frozen, an alternative perfect hashing implementation in C++ for problems also using constexpr keys. To our knowledge, this makes our library the overall fastest drop-in (i.e., with a similar API) alternative to std::unordered_map. On one arbitrarily chosen demo, we demonstrate runtimes <35% of PTHash and <89% gperf, state-of-the-art but not drop-in hashing libraries via external tools.

static_maps: consteval std::map and std::unordered_map Implementations in C++23

TL;DR

Using consteval from C++23, this library implements efficient, new versions of std::map and std::unordered_map for use when the keys are known at compile time, making this library the overall fastest drop-in hashing alternative to std::unordered_map.

Abstract

Using consteval from C++23, we implement efficient, new versions of std::map and std::unordered_map for use when the keys are known at compile time. We demonstrate superior performance of our unordered_map on three demonstration use-cases: Lookup of elemental mass from atomic symbol, lookup of amino acid from codon, and modification of stock prices from S&P 500 ticker symbols all produced runtimes <40%, <35%, <73% of the respective runtimes of the std implementations. Our library runimes were <80%, <45%, <97% of the lookup time of Frozen, an alternative perfect hashing implementation in C++ for problems also using constexpr keys. To our knowledge, this makes our library the overall fastest drop-in (i.e., with a similar API) alternative to std::unordered_map. On one arbitrarily chosen demo, we demonstrate runtimes <35% of PTHash and <89% gperf, state-of-the-art but not drop-in hashing libraries via external tools.
Paper Structure (35 sections, 5 equations, 3 figures, 1 table)

This paper contains 35 sections, 5 equations, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. Mapping
  3. Hashing
  4. Perfect hashing
  5. consteval maps
  6. Methods
  7. Implementation
  8. Secondary tables and RaggedArray
  9. Class hierarchy
  10. consteval generation of pseudorandom numbers
  11. Fast compile-time modulo
  12. Flexible SIZE_TYPE
  13. Avoidance of secondary hashing
  14. Factory construction
  15. Drop-in API
  16. ...and 20 more sections

Figures (3)

  • Figure 1: Runtimes of construction and lookup for static_maps::map against std::map on various demos. Lower is better.
  • Figure 2: Runtimes of construction and lookup for static_maps::map against std::map on various demos. Lower is better.
  • Figure 3: Runtimes compared to alternatives to drop-in replacements of unordered_map. Lower is better.