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  2. IBM hexadecimal floating-point - Wikipedia

    en.wikipedia.org/wiki/IBM_hexadecimal_floating-point

    Hexadecimal floating point (now called HFP by IBM) is a format for encoding floating-point numbers first introduced on the IBM System/360 computers, and supported on subsequent machines based on that architecture, [1] [2] [3] as well as machines which were intended to be application-compatible with System/360.

  3. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    The "decimal" data type of the C# and Python programming languages, and the decimal formats of the IEEE 754-2008 standard, are designed to avoid the problems of binary floating-point representations when applied to human-entered exact decimal values, and make the arithmetic always behave as expected when numbers are printed in decimal.

  4. Hexadecimal - Wikipedia

    en.wikipedia.org/wiki/Hexadecimal

    The hexadecimal system can express negative numbers the same way as in decimal: −2A to represent −42 10, −B01D9 to represent −721369 10 and so on. Hexadecimal can also be used to express the exact bit patterns used in the processor, so a sequence of hexadecimal digits may represent a signed or even a floating-point value.

  5. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    To approximate the greater range and precision of real numbers, we have to abandon signed integers and fixed-point numbers and go to a "floating-point" format. In the decimal system, we are familiar with floating-point numbers of the form (scientific notation): 1.1030402 × 10 5 = 1.1030402 × 100000 = 110304.02. or, more compactly: 1.1030402E5

  6. Single-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Single-precision_floating...

    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 2 31 − 1 = 2,147,483,647, whereas an IEEE 754 32-bit base-2 floating-point variable has a maximum value of (2 − 2 −23) × 2 127 ≈ 3.4028235 ...

  7. IEEE 754 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754

    The standard recommends providing conversions to and from external hexadecimal-significand character sequences, based on C99's hexadecimal floating point literals. Such a literal consists of an optional sign ( + or - ), the indicator "0x", a hexadecimal number with or without a period, an exponent indicator "p", and a decimal exponent with ...

  8. Hexadecimal floating point - Wikipedia

    en.wikipedia.org/wiki/Hexadecimal_floating_point

    Hexadecimal floating-point arithmetic in the Interdata 8/32 computer in the 1970s [1] Hexadecimal floating-point arithmetic in the Manchester MU5 computer in 1972 [ 2 ] Hexadecimal floating-point arithmetic in the Data General Eclipse S/200 computer in ca. 1974 [ 1 ]

  9. Half-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Half-precision_floating...

    Swift introduced half-precision floating point numbers in Swift 5.3 with the Float16 type. [20] OpenCL also supports half-precision floating point numbers with the half datatype on IEEE 754-2008 half-precision storage format. [21] As of 2024, Rust is currently working on adding a new f16 type for IEEE half-precision 16-bit floats. [22]