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  2. Multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Multiplication_algorithm

    First multiply the quarters by 47, the result 94 is written into the first workspace. Next, multiply cwt 12*47 = (2 + 10)*47 but don't add up the partial results (94, 470) yet. Likewise multiply 23 by 47 yielding (141, 940). The quarters column is totaled and the result placed in the second workspace (a trivial move in this case).

  3. Arbitrary-precision arithmetic - Wikipedia

    en.wikipedia.org/wiki/Arbitrary-precision_arithmetic

    The second most important decision is in the choice of the base of arithmetic, here ten. There are many considerations. The scratchpad variable d must be able to hold the result of a single-digit multiply plus the carry from the prior digit's multiply. In base ten, a sixteen-bit integer is certainly adequate as it allows up to 32767.

  4. Computational complexity of mathematical operations - Wikipedia

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

    Graphs of functions commonly used in the analysis of algorithms, showing the number of operations versus input size for each function. The following tables list the computational complexity of various algorithms for common mathematical operations.

  5. Permutation matrix - Wikipedia

    en.wikipedia.org/wiki/Permutation_matrix

    Multiplying a matrix M by either or on either the left or the right will permute either the rows or columns of M by either π or π −1.The details are a bit tricky. To begin with, when we permute the entries of a vector (, …,) by some permutation π, we move the entry of the input vector into the () slot of the output vector.

  6. Trachtenberg system - Wikipedia

    en.wikipedia.org/wiki/Trachtenberg_system

    Rule: to multiply by 12: Starting from the rightmost digit, double each digit and add the neighbor. (The "neighbor" is the digit on the right.) If the answer is greater than a single digit, simply carry over the extra digit (which will be a 1 or 2) to the next operation. The remaining digit is one digit of the final result.

  7. Matrix multiplication - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication

    A coordinate vector is commonly organized as a column matrix (also called a column vector), which is a matrix with only one column. So, a column vector represents both a coordinate vector, and a vector of the original vector space. A linear map A from a vector space of dimension n into a vector space of dimension m maps a column vector

  8. Strassen algorithm - Wikipedia

    en.wikipedia.org/wiki/Strassen_algorithm

    The left column visualizes the calculations necessary to determine the result of a 2x2 matrix multiplication. Naïve matrix multiplication requires one multiplication for each "1" of the left column. Each of the other columns (M1-M7) represents a single one of the 7 multiplications in the Strassen algorithm.

  9. Toom–Cook multiplication - Wikipedia

    en.wikipedia.org/wiki/Toom–Cook_multiplication

    Then multiply their values at these points to get points on the product polynomial. Finally interpolate to find its coefficients. Since deg(pq) = deg(p) + deg(q), we will need deg(p) + deg(q) + 1 = k m + k n − 1 points to determine the final result. Call this d. In the case of Toom-3, d = 5.