Converting Binary Floating-Point Numbers to Shortest Decimal Strings: An Experimental Review
Thursday, 29 Jan 2026·
,
Jaël Champagne Gareau
Daniel Lemire
Abstract
When sharing or logging numerical data, we must convert binary floating-point
numbers into their decimal string representations. For example, the number $\pi$
might become 3.1415927. Engineers have perfected many algorithms for producing
such accurate, short strings. We present an empirical comparison across
diverse hardware architectures and datasets. Cutting-edge techniques like
Schubfach and Dragonbox achieve up to a tenfold speedup over Steele and
White’s Dragon4, executing as few as 210 instructions per conversion compared
to Dragon4’s 1500–5000 instructions. Often per their specification, none of
the implementations we surveyed consistently produced the shortest possible
strings—some generate outputs up to 30% longer than optimal. We find that
standard library implementations in languages such as C++ and Swift execute
significantly more instructions than the fastest methods, with performance
gaps varying across CPU architectures and compilers. We suggest some
optimization targets for future research.
Type
Publication
Software: Practice and Experience

Authors
Postdoctoral Researcher in Computer Science
I am currently a postdoctoral researcher in computer science at Université
TÉLUQ, where my research focuses on speeding up the conversion of integer and
floating-point numbers into decimal strings. During my doctoral studies, I
designed algorithms and data structures that leverage modern computer
architectures to solve large instances of Markov decision processes (MDPs). In
my master’s research, I developed routing algorithms for electric vehicles
aimed at determining the optimal path between two points while minimizing
travel time (including driving, charging, and expected waiting time at
charging stations).
Authors