Hi, I was wondering if there is a better way of writing the function add_and_mul below, which is effectively (up to some scaling and addition) trying to compute the dot-product between the various row-vectors in two matrices? There must be a more elegant way of doing this, but I’m not yet seeing it… …

Note that you can fuse two of the loops there, and hoist some bounds checks to get another big speed-up: function add_and_mul3(X1, A, r, s, d) X2 = Matrix{Float64}(undef, size(X1)) @boundscheck checkbounds(A, axes(X2, 1), 1:d) @boundscheck checkbounds(X1, :, 1:d+1) @views X2[:,…

Reduce allocations in row-by-row dotproduct

New to Julia

Oscar_Smith February 5, 2025, 1:50pm 2

This will be a lot easier to write with for loops.

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Reduce allocations in row-by-row dotproduct

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