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  2. Quadruple-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Quadruple-precision...

    v. t. e. In 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, [1] but ...

  3. Double-precision floating-point format - Wikipedia

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

    Double-precision binary floating-point is a commonly used format on PCs, due to its wider range over single-precision floating point, in spite of its performance and bandwidth cost. It is commonly known simply as double. The IEEE 754 standard specifies a binary64 as having: Sign bit: 1 bit. Exponent: 11 bits.

  4. Mathematical operators and symbols in Unicode - Wikipedia

    en.wikipedia.org/wiki/Mathematical_operators_and...

    The Supplemental Mathematical Operators block (U+2A00–U+2AFF) contains various mathematical symbols, including N-ary operators, summations and integrals, intersections and unions, logical and relational operators, and subset/superset relations. Supplemental Mathematical Operators [1] Official Unicode Consortium code chart (PDF) 0.

  5. Single-precision floating-point format - Wikipedia

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

    Single-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 ...

  6. Minifloat - Wikipedia

    en.wikipedia.org/wiki/Minifloat

    A minifloat in 1 byte (8 bit) with 1 sign bit, 4 exponent bits and 3 significand bits (in short, a 1.4.3 minifloat) is demonstrated here. The exponent bias is defined as 7 to center the values around 1 to match other IEEE 754 floats [3] [4] so (for most values) the actual multiplier for exponent x is 2 x−7. All IEEE 754 principles should be ...

  7. Unum (number format) - Wikipedia

    en.wikipedia.org/wiki/Unum_(number_format)

    Unum (number format) Unums (universal numbers[1]) are a family of number formats and arithmetic for implementing real numbers on a computer, proposed by John L. Gustafson in 2015. [2] They are designed as an alternative to the ubiquitous IEEE 754 floating-point standard. The latest version is known as posits. [3]

  8. Integer overflow - Wikipedia

    en.wikipedia.org/wiki/Integer_overflow

    In computer programming, an integer overflow occurs when an arithmetic operation on integers attempts to create a numeric value that is outside of the range that can be represented with a given number of digits – either higher than the maximum or lower than the minimum representable value. The most common result of an overflow is that the ...

  9. Half-precision floating-point format - Wikipedia

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

    In 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 image processing and neural ...