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  2. Binary multiplier - Wikipedia

    en.wikipedia.org/wiki/Binary_multiplier

    In binary encoding each long number is multiplied by one digit (either 0 or 1), and that is much easier than in decimal, as the product by 0 or 1 is just 0 or the same number. Therefore, the multiplication of two binary numbers comes down to calculating partial products (which are 0 or the first number), shifting them left, and then adding them ...

  3. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    The IEEE standard stores the sign, exponent, and significand in separate fields of a floating point word, each of which has a fixed width (number of bits). The two most commonly used levels of precision for floating-point numbers are single precision and double precision.

  4. Computer performance by orders of magnitude - Wikipedia

    en.wikipedia.org/wiki/Computer_performance_by...

    1×10 −1: multiplication of two 10-digit numbers by a 1940s electromechanical desk calculator [1] 3×10 −1: multiplication on Zuse Z3 and Z4, first programmable digital computers, 1941 and 1945 respectively; 5×10 −1: computing power of the average human mental calculation [clarification needed] for multiplication using pen and paper

  5. Arbitrary-precision arithmetic - Wikipedia

    en.wikipedia.org/wiki/Arbitrary-precision_arithmetic

    For multiplication, the most straightforward algorithms used for multiplying numbers by hand (as taught in primary school) require (N 2) operations, but multiplication algorithms that achieve O(N log(N) log(log(N))) complexity have been devised, such as the Schönhage–Strassen algorithm, based on fast Fourier transforms, and there are also ...

  6. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    On a typical computer system, a double-precision (64-bit) binary floating-point number has a coefficient of 53 bits (including 1 implied bit), an exponent of 11 bits, and 1 sign bit. Since 2 10 = 1024, the complete range of the positive normal floating-point numbers in this format is from 2 −1022 ≈ 2 × 10 −308 to approximately 2 1024 ≈ ...

  7. Computational complexity of mathematical operations - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    Here, complexity refers to the time complexity of performing computations on a multitape Turing machine. [1] See big O notation for an explanation of the notation used. Note: Due to the variety of multiplication algorithms, () below stands in for the complexity of the chosen multiplication algorithm.

  8. Booth's multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Booth's_multiplication...

    This then follows the implementation described above, with modifications in determining the bits of A and S; e.g., the value of m, originally assigned to the first x bits of A, will be now be extended to x+1 bits and assigned to the first x+1 bits of A. Below, the improved technique is demonstrated by multiplying −8 by 2 using 4 bits for the ...

  9. HP-16C - Wikipedia

    en.wikipedia.org/wiki/HP-16C

    It also deals with floating-point decimal numbers. To accommodate long integers, the display can be 'windowed' by shifting it left and right. For consistency with the computer the programmer is working with, the word size can be set to different values from 1 to 64 bits.