Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

Double-precision floating-point format

Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point.

Standards, IEEE 754 double-precision binary floating-point format: binary64 & Implementations

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around Double-precision floating-point format. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

IEEE 754 double-precision binary floating-point format: binary64

Sign bitExponentSignificandPrecisionSigned zero
22 related topics

Implementations

SSE2Arithmetic typesC99Double roundingCommon Lisp
14 related topics

Overview

Floating-pointNumber formatBitsRadix pointSingle precision
14 related topics

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

IEEE 754 double-precision binary floating-point format: binary64

Implementations

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Double-precision floating-point format

Nodes54
Edges53
Triples0
Avg. degree1.96
Density0.037037
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

floating-point precision ieee 754 double-precision format standard range numbers exponent significand number double data representation floating point integers using may

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.