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  2. 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.

  3. Type conversion - Wikipedia

    en.wikipedia.org/wiki/Type_conversion

    C and C++ perform such promotion for objects of Boolean, character, wide character, enumeration, and short integer types which are promoted to int, and for objects of type float, which are promoted to double. Unlike some other type conversions, promotions never lose precision or modify the value stored in the object. In Java:

  4. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    Any integer with absolute value less than 2 24 can be exactly represented in the single-precision format, and any integer with absolute value less than 2 53 can be exactly represented in the double-precision format. Furthermore, a wide range of powers of 2 times such a number can be represented.

  5. Decimal data type - Wikipedia

    en.wikipedia.org/wiki/Decimal_data_type

    C# has a built-in data type decimal consisting of 128 bits resulting in 28–29 significant digits. It has an approximate range of ±1.0 × 10 −28 to ±7.9228 × 10 28. [1] Starting with Python 2.4, Python's standard library includes a Decimal class in the module decimal. [2]

  6. decimal32 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Decimal32_floating-point...

    The resulting 'raw' exponent is a 8 bit binary integer where the leading bits are not '11', thus values 0 ... 1011 1111 b = 0 ... 191 d , appr. bias is to be subtracted. The resulting significand could be a positive binary integer of 24 bits up to 1001 1111111111 1111111111 b = 10485759 d , but values above 10 7 − 1 = 9 999 999 = 98967F 16 ...

  7. bfloat16 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Bfloat16_floating-point_format

    From binary32 to bfloat16. When bfloat16 was first introduced as a storage format, [15] the conversion from IEEE 754 binary32 (32-bit floating point) to bfloat16 is truncation (round toward 0). Later on, when it becomes the input of matrix multiplication units, the conversion can have various rounding mechanisms depending on the hardware platforms.

  8. IEEE 754 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754

    rounding rules: properties to be satisfied when rounding numbers during arithmetic and conversions; operations: arithmetic and other operations (such as trigonometric functions) on arithmetic formats; exception handling: indications of exceptional conditions (such as division by zero, overflow, etc.)

  9. Rounding - Wikipedia

    en.wikipedia.org/wiki/Rounding

    In the example from "Double rounding" section, rounding 9.46 to one decimal gives 9.4, which rounding to integer in turn gives 9. With binary arithmetic, this rounding is also called "round to odd" (not to be confused with "round half to odd"). For example, when rounding to 1/4 (0.01 in binary), x = 2.0 ⇒ result is 2 (10.00 in binary)