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  2. Fixed-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_arithmetic

    A fixed-point representation of a fractional number is essentially an integer that is to be implicitly multiplied by a fixed scaling factor. For example, the value 1.23 can be stored in a variable as the integer value 1230 with implicit scaling factor of 1/1000 (meaning that the last 3 decimal digits are implicitly assumed to be a decimal fraction), and the value 1 230 000 can be represented ...

  3. Quadruple-precision floating-point format - Wikipedia

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

    It had one sign bit, a 15-bit exponent and 112-fraction bits, however the layout in memory was significantly different from IEEE quadruple precision and the exponent bias also differed. Only a few of the earliest VAX processors implemented H Floating-point instructions in hardware, all the others emulated H Floating-point in software.

  4. Arbitrary-precision arithmetic - Wikipedia

    en.wikipedia.org/wiki/Arbitrary-precision_arithmetic

    The computer may also offer facilities for splitting a product into a digit and carry without requiring the two operations of mod and div as in the example, and nearly all arithmetic units provide a carry flag which can be exploited in multiple-precision addition and subtraction. This sort of detail is the grist of machine-code programmers, and ...

  5. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    The sum of the exponent bias (127) and the exponent (1) is 128, so this is represented in the single-precision format as 0 10000000 10010010000111111011011 (excluding the hidden bit) = 40490FDB [27] as a hexadecimal number. An example of a layout for 32-bit floating point is and the 64-bit ("double") layout is similar.

  6. IEEE 754-1985 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754-1985

    The positive and negative normalized numbers closest to zero (represented with the binary value 1 in the exponent field and 0 in the fraction field) are ±1 × 2 −126 ≈ ±1.17549 × 10 −38 The finite positive and finite negative numbers furthest from zero (represented by the value with 254 in the exponent field and all 1s in the fraction ...

  7. Modular exponentiation - Wikipedia

    en.wikipedia.org/wiki/Modular_exponentiation

    The most direct method of calculating a modular exponent is to calculate b e directly, then to take this number modulo m. Consider trying to compute c, given b = 4, e = 13, and m = 497: c ≡ 4 13 (mod 497) One could use a calculator to compute 4 13; this comes out to 67,108,864.

  8. Double-precision floating-point format - Wikipedia

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

    With the 52 bits of the fraction (F) significand appearing in the memory format, the total precision is therefore 53 bits (approximately 16 decimal digits, 53 log 10 (2) ≈ 15.955). The bits are laid out as follows: The real value assumed by a given 64-bit double-precision datum with a given biased exponent and a 52-bit fraction is

  9. Rational data type - Wikipedia

    en.wikipedia.org/wiki/Rational_data_type

    Python: The standard library includes a Fraction class in the module fractions. [6] Ruby: native support using special syntax. Smalltalk represents rational numbers using a Fraction class in the form p/q where p and q are arbitrary size integers. Applying the arithmetic operations *, +, -, /, to fractions returns a reduced fraction. With ...