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  2. Power of two - Wikipedia

    en.wikipedia.org/wiki/Power_of_two

    2 63 − 1, a common maximum value (equivalently the number of positive values) for a signed 64-bit integer in programming languages. 2 64 = 18,446,744,073,709,551,616 The number of distinct values representable in a single word on a 64-bit processor. Or, the number of values representable in a doubleword on a 32-bit processor.

  3. 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.

  4. Wheat and chessboard problem - Wikipedia

    en.wikipedia.org/wiki/Wheat_and_chessboard_problem

    The number of grains of wheat on the second half of the chessboard is 2 32 + 2 33 + 2 34 + ... + 2 63, for a total of 2 642 32 grains. This is equal to the square of the number of grains on the first half of the board, plus itself. The first square of the second half alone contains one more grain than the entire first half.

  5. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    2.3434E−6 = 2.3434 × 10 −6 = 2.3434 × 0.000001 = 0.0000023434. The advantage of this scheme is that by using the exponent we can get a much wider range of numbers, even if the number of digits in the significand, or the "numeric precision", is much smaller than the range. Similar binary floating-point formats can be defined for computers.

  6. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    The otherwise binary Wang VS machine supported a 64-bit decimal floating-point format in 1977. [2] The Motorola 68881 supported a format with 17 digits of mantissa and 3 of exponent in 1984, with the floating-point support library for the Motorola 68040 processor providing a compatible 96-bit decimal floating-point storage format in 1990.

  7. IEEE 754 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754

    In the table above, integer values are exact, whereas values in decimal notation (e.g. 1.0) are rounded values. ... (4 log 2 (k)) − 13. The existing 64- and 128-bit ...

  8. AOL

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    The search engine that helps you find exactly what you're looking for. Find the most relevant information, video, images, and answers from all across the Web.

  9. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    This alternative definition is significantly more widespread: machine epsilon is the difference between 1 and the next larger floating point number.This definition is used in language constants in Ada, C, C++, Fortran, MATLAB, Mathematica, Octave, Pascal, Python and Rust etc., and defined in textbooks like «Numerical Recipes» by Press et al.