In How to optimise Julia code: A practical guide , Jakob Nissen suggests that one way to optimize code + reduce allocations is to Preallocate buffers once and reuse them multiple times I’m wondering if someone has a walkthrough of an actual example comparing a “repeatedly allocate” solution to a “…

[image] philip: Let’s say calculate_and_use has to be called millions of times by some function, so each time there’s an allocation of a ResultData object which is then thrown away and, voila, re-allocated a split second later. struct objects are not generally allocated on the heap, so you do…

Fair enough and thanks; that’s interesting! Alas I was being lazy and the reality is that several of the many, many objects I’m repeatedly allocating are Dicts and others are Arrays. I apologize that I think I oversimplified in my efforts to make the MWE M enough to be legible, but I think I still…

Hard to say more without a specific example, but the generic advice is (a) avoid allocating temporary arrays (or other mutable data structures) at all in your inner loops (work in place, use tuples and staticarrays, ditch “vectorize everything” habits from Matlab and Numpy, …), and otherwise write i…

This is great advice. I think my question could alternately be phrased as “what does work in place mean”? Like is there an example / blog post / similar somewhere that can show the “in-place” version side-by-side with the “not-in-place” version? For example above, if we pretend temp is a mutable d…

[A.Yazdiha] Mutating function in Julia (function that modifies its arguments) julia asked by A.Yazdiha on 01:00PM - 02 Sep 16 UTC

[image] philip: I think my question could alternately be phrased as “what does work in place mean”? There’s actually a Wikipedia page on the topic: In-place algorithm In computer science, an in-place algorithm is an algorithm that operates directly on the input data structure with…

@stevengj @nsajko thanks both for the links. I do understand how to mutate an object passed as an argument. I’m trying to ask about the paradigm. Is the ideal paradigm to generate the object to serve as the placeholder/buffer at the global level? One function-call up? Different advice for different…

Just a silly example of converting an algorithm to in place would be function add_one(arr) return arr .+ 1 end # In Julia, we add `!` to the end of in place/ mutating function names by convention function add_one!(arr) for i in eachindex(arr) arr[i] = arr[i] + 1 end end

Thanks all. May I ask that we put this question on hold for a second and I’m going to provide a bigger MWE. I’m clearly not explaining the question clearly. Stay tuned. :slight_smile:

[image] philip: Is the ideal paradigm to generate the object to serve as the placeholder/buffer at the global level? One function-call up? Almost certainly not global. It just needs to be somewhere outside of your critical inner loop(s).

How to preallocate and reuse buffers for oft-repeated computation?

General Usage

lmiq June 27, 2023, 11:57pm 12

You can find some examples on this thread, with the most common patterns to avoid, and what to do: Common allocation mistakes

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How to preallocate and reuse buffers for oft-repeated computation?

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