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  2. Double-precision floating-point format - Wikipedia

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

    00000000000 2 =000 16 is used to represent a signed zero (if F = 0) and subnormal numbers (if F ≠ 0); and; 11111111111 2 =7ff 16 is used to represent ∞ (if F = 0) and NaNs (if F ≠ 0), where F is the fractional part of the significand. All bit patterns are valid encoding. Except for the above exceptions, the entire double-precision number ...

  3. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal to 0) is used. For IEEE standard where the base β {\displaystyle \beta } is 2 {\displaystyle 2} , this means when there is a tie it is rounded so that the last digit is equal to 0 {\displaystyle 0} .

  4. decimal64 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Decimal64_floating-point...

    This is pretty efficient, because 2 10 = 1024, is only little more than needed to still contain all numbers from 0 to 999. Both alternatives provide exactly the same set of representable numbers: 16 digits of significand and 3 × 2 8 = 768 possible decimal exponent values.

  5. Quadruple-precision floating-point format - Wikipedia

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

    As the magnitude of the value decreases, the amount of extra precision also decreases. Therefore, the smallest number in the normalized range is narrower than double precision. The smallest number with full precision is 1000...0 2 (106 zeros) × 2 −1074, or 1.000...0 2 (106 zeros) × 2 −968. Numbers whose magnitude is smaller than 2 −1021 ...

  6. decimal32 floating-point format - Wikipedia

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

    Be aware that the bit numbering used here for e.g. b 9 … b 0 is in opposite direction than that used in the document for the IEEE 754 standard b 0 … b 9, add. the decimal digits are numbered 0-base here while in opposite direction and 1-based in the IEEE 754 paper. The bits on white background are not counting for the value, but signal how ...

  7. Octuple-precision floating-point format - Wikipedia

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

    The minimum strictly positive (subnormal) value is 2 −262378 ≈ 10 −78984 and has a precision of only one bit. The minimum positive normal value is 2 −262142 ≈ 2.4824 × 10 −78913. The maximum representable value is 2 262144 − 2 261907 ≈ 1.6113 × 10 78913.

  8. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    For numbers with a base-2 exponent part of 0, i.e. numbers with an absolute value higher than or equal to 1 but lower than 2, an ULP is exactly 2 −23 or about 10 −7 in single precision, and exactly 2 −53 or about 10 −16 in double precision. The mandated behavior of IEEE-compliant hardware is that the result be within one-half of a ULP.

  9. Unit in the last place - Wikipedia

    en.wikipedia.org/wiki/Unit_in_the_last_place

    Here we start with 0 in single precision (binary32) and repeatedly add 1 until the operation does not change the value. Since the significand for a single-precision number contains 24 bits, the first integer that is not exactly representable is 2 24 +1, and this value rounds to 2 24 in round to nearest, ties to even.