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  2. Single-precision floating-point format - Wikipedia

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

    If an IEEE 754 single-precision number is converted to a decimal string with at least 9 significant digits, and then converted back to single-precision representation, the final result must match the original number. [6] The sign bit determines the sign of the number, which is the sign of the significand as well. "1" stands for negative.

  3. 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 ...

  4. Quadruple-precision floating-point format - Wikipedia

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

    The range of a double-double remains essentially the same as the double-precision format because the exponent has still 11 bits, [4] significantly lower than the 15-bit exponent of IEEE quadruple precision (a range of 1.8 × 10 308 for double-double versus 1.2 × 10 4932 for binary128).

  5. Integer overflow - Wikipedia

    en.wikipedia.org/wiki/Integer_overflow

    The register width of a processor determines the range of values that can be represented in its registers. Though the vast majority of computers can perform multiple-precision arithmetic on operands in memory, allowing numbers to be arbitrarily long and overflow to be avoided, the register width limits the sizes of numbers that can be operated on (e.g., added or subtracted) using a single ...

  6. Unum (number format) - Wikipedia

    en.wikipedia.org/wiki/Unum_(number_format)

    convert double to posit; convert posit to double; cast unsigned integer to posit; It works for 16-bit posits with one exponent bit and 8-bit posit with zero exponent bit. Support for 32-bit posits and flexible type (2-32 bits with two exponent bits) is pending validation. It supports x86_64 systems.

  7. Two's complement - Wikipedia

    en.wikipedia.org/wiki/Two's_complement

    Two's complement is the most common method of representing signed (positive, negative, and zero) integers on computers, [1] and more generally, fixed point binary values. Two's complement uses the binary digit with the greatest value as the sign to indicate whether the binary number is positive or negative; when the most significant bit is 1 the number is signed as negative and when the most ...

  8. 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.

  9. Half-precision floating-point format - Wikipedia

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

    If the hardware has instructions to compute half-precision math, it is often faster than single or double precision. If the system has SIMD instructions that can handle multiple floating-point numbers within one instruction, half precision can be twice as fast by operating on twice as many numbers simultaneously. [13]