I am trying to understand why I can’t use @turbo in part of my code. I can reduce the issue to the following example using LoopVectorization f = [15, 13, 12, 10, 9, 7, 5, 4, 2, 1] y0 = zeros(16) y1 = zeros(16) for i = 1:10 y0[f[i]] += 1.0 y0[f[i] + 1] += 2.0 end @turbo for i = 1:10 y…

[image] james3: Why is it not appropriate to use it in this case? From the @turbo documentation : It assumes that loop iterations are independent. Here, the loop iterations are somewhat dependent (though they can be executed in any order) because different iterations modify the same y1 ele…

Why is this loop type not supported by LoopVectorization?

New to Julia

DNF August 16, 2023, 10:49pm 6

I would guess that invariance to shuffling is not enough either. The different iterations should be able to execute simultaneously, so check for possible data races.

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Why is this loop type not supported by LoopVectorization?

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