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Number parsing at a gigabyte per second

Daniel LemirePublished May 11, 2021
DOI Publisher
Researcher verdict
Context only
Use as context only
Benchmark evidence
Missing
Not verified yet
Time to first repro
A few days
Plan setup time
Risk flags
1
Review before use

Abstract

Domain fit: AI-adjacent · Paper appears method- or tooling-adjacent to AI workflows with partial ecosystem coverage.

Abstract With disks and networks providing gigabytes per second, parsing decimal numbers from strings becomes a bottleneck. We consider the problem of parsing decimal numbers to the nearest binary floating‐point value. The general problem requires variable‐precision arithmetic. However, we need at most 17 digits to represent 64‐bit standard floating‐point numbers (IEEE 754). Thus, we can represent the decimal significand with a single 64‐bit word. By combining the significand and precomputed tables, we can compute the nearest floating‐point number using as few as one or two 64‐bit multiplications. Our implementation can be several times faster than conventional functions present in standard C libraries on modern 64‐bit systems (Intel, AMD, ARM, and POWER9). Our work is available as open source software used by major systems such as Apache Arrow and Yandex ClickHouse. The Go standard library has adopted a version of our approach.

Results and benchmarks

Freshness tier: cold
Abstract With disks and networks providing gigabytes per second, parsing decimal numbers from strings becomes a bottleneck.

Implementation

No direct implementation yet

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Implementation evidence summary
Confidence: low

simdjson/simdjson is the closest maintained adjacent implementation (Strong overlap with paper title keywords). It is not paper-verified; validate algorithm and evaluation setup against the paper before trusting reported metrics. Community adoption signal: 24181 GitHub stars.

Reproduction risks
  • Adjacent implementations are not paper-verified
  • Recommended repository is adjacent and not paper-verified.
  • Adjacent implementation match confidence is low.

Reproduction readiness

Time to first repro: days
Last checked: Aug 25, 2026

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No verified implementation available

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Hardware requirements

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Repositories and ecosystem

Closest related implementations

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  • simdjson/simdjson Adjacent · Confidence: Low · 24,181 stars

    Strong overlap with paper title keywords

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Research context

2

Citations

28

References

Tasks

Decimal, Computer science, Parsing, Arithmetic, IEEE floating point, Bottleneck, Floating point, Binary number

Methods

Algorithm

Domains

Computational Theory and Mathematics

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