Virgule flottantevignette|Comme la notation scientifique, le nombre à virgule flottante a une mantisse et un exposant. La virgule flottante est une méthode d'écriture de nombres fréquemment utilisée dans les ordinateurs, équivalente à la notation scientifique en numération binaire. Elle consiste à représenter un nombre par : un signe (égal à −1 ou 1) ; une mantisse (aussi appelée significande) ; et un exposant (entier relatif, généralement borné).
Decimal floating pointDecimal floating-point (DFP) arithmetic refers to both a representation and operations on decimal floating-point numbers. Working directly with decimal (base-10) fractions can avoid the rounding errors that otherwise typically occur when converting between decimal fractions (common in human-entered data, such as measurements or financial information) and binary (base-2) fractions. The advantage of decimal floating-point representation over decimal fixed-point and integer representation is that it supports a much wider range of values.
Double-precision floating-point formatDouble-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 dynamic range of numeric values by using a floating radix point. Floating point is used to represent fractional values, or when a wider range is needed than is provided by fixed point (of the same bit width), even if at the cost of precision. Double precision may be chosen when the range or precision of single precision would be insufficient.
Single-precision floating-point formatSingle-precision floating-point format (sometimes called FP32 or float32) is a computer number format, usually occupying 32 bits in computer memory; it represents a wide dynamic range of numeric values by using a floating radix point. A floating-point variable can represent a wider range of numbers than a fixed-point variable of the same bit width at the cost of precision. A signed 32-bit integer variable has a maximum value of 231 − 1 = 2,147,483,647, whereas an IEEE 754 32-bit base-2 floating-point variable has a maximum value of (2 − 2−23) × 2127 ≈ 3.
Quadruple-precision floating-point formatIn computing, quadruple precision (or quad precision) is a binary floating point–based computer number format that occupies 16 bytes (128 bits) with precision at least twice the 53-bit double precision. This 128-bit quadruple precision is designed not only for applications requiring results in higher than double precision, but also, as a primary function, to allow the computation of double precision results more reliably and accurately by minimising overflow and round-off errors in intermediate calculations and scratch variables.
Half-precision floating-point formatIn computing, half precision (sometimes called FP16 or float16) is a binary floating-point computer number format that occupies 16 bits (two bytes in modern computers) in computer memory. It is intended for storage of floating-point values in applications where higher precision is not essential, in particular and neural networks. Almost all modern uses follow the IEEE 754-2008 standard, where the 16-bit base-2 format is referred to as binary16, and the exponent uses 5 bits.
Extended precisionExtended precision refers to floating-point number formats that provide greater precision than the basic floating-point formats. Extended precision formats support a basic format by minimizing roundoff and overflow errors in intermediate values of expressions on the base format. In contrast to extended precision, arbitrary-precision arithmetic refers to implementations of much larger numeric types (with a storage count that usually is not a power of two) using special software (or, rarely, hardware).
Virgule fixeEn informatique, une représentation d'un nombre en virgule fixe est un type de donnée correspondant à un nombre qui possède (en base deux ou en base dix) un nombre fixe de chiffres après la virgule. Les nombres en virgule fixe sont utiles pour représenter des quantités fractionnaires dans un format utilisant le complément à deux quand le processeur de l'ordinateur n'a aucune unité de calcul en virgule flottante ou quand une virgule fixe permet d'augmenter la vitesse d'exécution ou d'améliorer l'exactitude des calculs.
Unité de calcul en virgule flottantethumbnail|Le Motorola 68882, un coprocesseur arithmétique. Une unité de calcul en virgule flottante (UVF, en anglais floating-point unit, FPU) est une partie d'un processeur, spécialement conçue pour effectuer des opérations sur des nombres à virgule flottante. Tous les processeurs incorporent au moins l'addition, la soustraction et la multiplication. L'opération fused multiply–add (multiplication suivie d'une addition, avec un seul arrondi), requise par la norme IEEE 754 dans sa révision de 2008, est de plus en plus implémentée.
Kahan summation algorithmIn numerical analysis, the Kahan summation algorithm, also known as compensated summation, significantly reduces the numerical error in the total obtained by adding a sequence of finite-precision floating-point numbers, compared to the obvious approach. This is done by keeping a separate running compensation (a variable to accumulate small errors), in effect extending the precision of the sum by the precision of the compensation variable.
