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
Abstract With disks and networks providing gigabytes per second, parsing decimal numbers from strings becomes a bottleneck.
Benchmark evidence is limited
Evidence graph: 3 refs, 3 links.
Utility signals: depth 70/100, grounding 75/100, status medium.
Implementation
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Time to first repro: a few days
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.
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Reproduction readiness
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Hardware requirements
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Validation caveat
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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Hugging Face artifacts
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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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