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  2. libfixmath - Wikipedia

    en.wikipedia.org/wiki/Libfixmath

    libfixmath is a platform-independent fixed-point math library aimed at developers wanting to perform fast non-integer math on platforms lacking a (or with a low performance) FPU.

  3. List of arbitrary-precision arithmetic software - Wikipedia

    en.wikipedia.org/wiki/List_of_arbitrary...

    Python: the built-in int (3.x) / long (2.x) integer type is of arbitrary precision. The Decimal class in the standard library module decimal has user definable precision and limited mathematical operations (exponentiation

  4. Arbitrary-precision arithmetic - Wikipedia

    en.wikipedia.org/wiki/Arbitrary-precision_arithmetic

    The 1620 was a decimal-digit machine which used discrete transistors, yet it had hardware (that used lookup tables) to perform integer arithmetic on digit strings of a length that could be from two to whatever memory was available. For floating-point arithmetic, the mantissa was restricted to a hundred digits or fewer, and the exponent was ...

  5. Floating-point error mitigation - Wikipedia

    en.wikipedia.org/wiki/Floating-point_error...

    Huberto M. Sierra noted in his 1956 patent "Floating Decimal Point Arithmetic Control Means for Calculator": [1] Thus under some conditions, the major portion of the significant data digits may lie beyond the capacity of the registers.

  6. Half-precision floating-point format - Wikipedia

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

    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] Julia provides support for half-precision floating point numbers with the Float16 type. [23]

  7. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    The IEEE standard stores the sign, exponent, and significand in separate fields of a floating point word, each of which has a fixed width (number of bits). The two most commonly used levels of precision for floating-point numbers are single precision and double precision.

  8. Double-precision floating-point format - Wikipedia

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

    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. Double precision may be chosen when the range or precision of single precision would be insufficient.

  9. Single-precision floating-point format - Wikipedia

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

    Single precision is termed REAL in Fortran; [1] SINGLE-FLOAT in Common Lisp; [2] float in C, C++, C# and Java; [3] Float in Haskell [4] and Swift; [5] and Single in Object Pascal , Visual Basic, and MATLAB. However, float in Python, Ruby, PHP, and OCaml and single in versions of Octave before 3.2 refer to double-precision numbers.