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[-] kbotc@lemmy.world 15 points 2 months ago

Dynamically sized but stored contiguously makes the systems performance engineer in me weep. If the lists get big, the kernel is going to do so much churn.

[-] Killing_Spark@feddit.de 15 points 2 months ago

Contiguous storage is very fast in terms of iteration though often offsetting the cost of allocation

[-] Slotos@feddit.nl 7 points 2 months ago

Modern CPUs are also extremely efficient at dealing with contiguous data structures. Branch prediction and caching get to shine on them.

Avoiding memory access or helping CPU access it all upfront switches physical domain of computation.

[-] IAmVeraGoodAtThis@lemmy.blahaj.zone 7 points 2 months ago* (last edited 2 months ago)

Which is why you should:

  1. Preallocate the vector if you can guesstimate the size
  2. Use a vector library that won't reallocate the entire vector on every single addition (like Rust, whose Vec doubles in size every time it runs out of space)

Memory is fairly cheap. Allocation time not so much.

[-] yetiftw@lemmy.world 4 points 2 months ago

matlab likes to pick the smallest available spot in memory to store a list, so for loops that increase the size of a matrix it's recommended to preallocate the space using a matrix full of zeros!

[-] tamal3@lemmy.world 2 points 2 months ago

Is that churn or chum? (RN or M)

this post was submitted on 28 Apr 2024
503 points (96.8% liked)

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