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  2. Schönhage–Strassen algorithm - Wikipedia

    en.wikipedia.org/wiki/Schönhage–Strassen...

    The Schönhage–Strassen algorithm is based on the fast Fourier transform (FFT) method of integer multiplication. This figure demonstrates multiplying 1234 × 5678 = 7006652 using the simple FFT method. Base 10 is used in place of base 2 w for illustrative purposes.

  3. Multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Multiplication_algorithm

    5 is halved (2.5) and 6 is doubled (12). The fractional portion is discarded (2.5 becomes 2). The figure in the left column (2) is even, so the figure in the right column (12) is discarded. 2 is halved (1) and 12 is doubled (24). All not-scratched-out values are summed: 3 + 6 + 24 = 33. The method works because multiplication is distributive, so:

  4. Toom–Cook multiplication - Wikipedia

    en.wikipedia.org/wiki/Toom–Cook_multiplication

    Toom-1.5 (k m = 2, k n = 1) is still degenerate: it recursively reduces one input by halving its size, but leaves the other input unchanged, hence we can make it into a multiplication algorithm only if we supply a 1 × n multiplication algorithm as a base case (whereas the true Toom–Cook algorithm reduces to constant-size base cases). It ...

  5. Karatsuba algorithm - Wikipedia

    en.wikipedia.org/wiki/Karatsuba_algorithm

    Karatsuba multiplication of az+b and cz+d (boxed), and 1234 and 567 with z=100. Magenta arrows denote multiplication, amber denotes addition, silver denotes subtraction and cyan denotes left shift. (A), (B) and (C) show recursion with z=10 to obtain intermediate values. The Karatsuba algorithm is a fast multiplication algorithm.

  6. Trachtenberg system - Wikipedia

    en.wikipedia.org/wiki/Trachtenberg_system

    The method for general multiplication is a method to achieve multiplications with low space complexity, i.e. as few temporary results as possible to be kept in memory. . This is achieved by noting that the final digit is completely determined by multiplying the last digit of the multiplic

  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, M ( n ) {\displaystyle M(n)} below stands in for the complexity of the chosen multiplication algorithm.

  8. Multiplication sign - Wikipedia

    en.wikipedia.org/wiki/Multiplication_sign

    The multiplication sign (×), also known as the times sign or the dimension sign, is a mathematical symbol used to denote the operation of multiplication, which results in a product. [ 1 ] The symbol is also used in botany , in botanical hybrid names .

  9. Lunar arithmetic - Wikipedia

    en.wikipedia.org/wiki/Lunar_arithmetic

    Lunar arithmetic, formerly called dismal arithmetic, [1] [2] is a version of arithmetic in which the addition and multiplication operations on digits are defined as the max and min operations. Thus, in lunar arithmetic, + = {,} = and = {,} =