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  2. Matrix multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication...

    The definition of matrix multiplication is that if C = AB for an n × m matrix A and an m × p matrix B, then C is an n × p matrix with entries = =. From this, a simple algorithm can be constructed which loops over the indices i from 1 through n and j from 1 through p, computing the above using a nested loop:

  3. Loop fission and fusion - Wikipedia

    en.wikipedia.org/wiki/Loop_fission_and_fusion

    Loop fission (or loop distribution) is a compiler optimization in which a loop is broken into multiple loops over the same index range with each taking only a part of the original loop's body. [ 1 ] [ 2 ] The goal is to break down a large loop body into smaller ones to achieve better utilization of locality of reference .

  4. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]

  5. Loop nest optimization - Wikipedia

    en.wikipedia.org/wiki/Loop_nest_optimization

    Loop tiling partitions a loop's iteration space into smaller chunks or blocks, so as to help ensure data used in a loop stays in the cache until it is reused. The partitioning of loop iteration space leads to partitioning of a large array into smaller blocks, thus fitting accessed array elements into cache size, enhancing cache reuse and eliminating cache size requirements.

  6. Power iteration - Wikipedia

    en.wikipedia.org/wiki/Power_iteration

    #!/usr/bin/env python3 import numpy as np def power_iteration (A, num_iterations: int): # Ideally choose a random vector # To decrease the chance that our vector # Is orthogonal to the eigenvector b_k = np. random. rand (A. shape [1]) for _ in range (num_iterations): # calculate the matrix-by-vector product Ab b_k1 = np. dot (A, b_k) # calculate the norm b_k1_norm = np. linalg. norm (b_k1 ...

  7. For loop - Wikipedia

    en.wikipedia.org/wiki/For_loop

    The loop counter is used to decide when the loop should terminate and for the program flow to continue to the next instruction after the loop. A common identifier naming convention is for the loop counter to use the variable names i , j , and k (and so on if needed), where i would be the most outer loop, j the next inner loop, etc.

  8. NYT ‘Connections’ Hints and Answers Today, Friday, January 17

    www.aol.com/nyt-connections-hints-answers-today...

    Spoilers ahead! We've warned you. We mean it. Read no further until you really want some clues or you've completely given up and want the answers ASAP. Get ready for all of today's NYT ...

  9. Kahan summation algorithm - Wikipedia

    en.wikipedia.org/wiki/Kahan_summation_algorithm

    y = 2.71828 - (-0.0415900) Most digits meet, since c is of a size similar to y. = 2.75987 The shortfall (low-order digits lost) of previous iteration successfully reinstated. t = 10003.1 + 2.75987 But still only few meet the digits of sum. = 10005.85987 Normalization done, next round to six digits.

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