Instead of using for-loops to perform 2D convolution on images (or any other 2D matrices) we can convert the filter to a Toeplitz matrix and image to a vector and do the convolution just by one matrix multiplication (and of course some post-processing on the result of this multiplication to get the ...
Broadcasting a vector into a matrix. A miniature multiplication table. In this example, we multiply a one-dimensional vector (V) of size (3,1) and the transposed version of it, which is of size (1,3), and get back a (3,3) matrix, which is the outer product of V.If you still find this confusing, the next illustration breaks down the process into 2 steps, making it clearer:
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May 18, 2015 · Three dimensional arrays? As in vectors of two dimensional arrays? Something like, [math]A = (\alpha_1, \alpha_2, ..., \alpha_n)[/math], where [math]\alpha_1, \alpha ...
Nov 23, 2011 · The NVIDIA GPU Computing SDK has a few examples of multiplication, which for all intents and purposes is the same as addition. You shouldn't need texture memory for this. You are essentially accessing the whole chunk of memory in a linear manner, which is fine from normal global memory.
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for matrix multiplication and more complicated matrix computations have been compared and implemented on both 1D ,  and 2D systolic arrays , , . In , the concept of a general systolic array and a taxonomy of systolic array designs is presented. With increasing memory walls, recent approaches
2D matrix to 1D array and back again C++ uses row major order: n x m, which are the number of rows and columns also called the height and the width a(i,j) can be ﬂatten to 1D array b(k)