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Reduce memory usage of tracking instruction callstacks in dfg.locations #6603

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TomAFrench opened this issue Nov 22, 2024 · 2 comments · May be fixed by #6791
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Reduce memory usage of tracking instruction callstacks in dfg.locations #6603

TomAFrench opened this issue Nov 22, 2024 · 2 comments · May be fixed by #6791
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@TomAFrench
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We currently track the callstacks for each instruction in the locations field of the DataflowGraph:

locations: HashMap<InstructionId, CallStack>,

Heaptrack is reporting that inserting entries into this hashmap is using 17% of the compiler's peak memory.

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We should definitely not require 157MB of memory in order to track this as the number of unique callstacks is going to be relatively low. It should be relatively easy to rework this so that we don't track N different instances of the same callstack.

@github-project-automation github-project-automation bot moved this to 📋 Backlog in Noir Nov 22, 2024
@jfecher
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jfecher commented Nov 22, 2024

Hmm, are we sure it's coming from N different instances of the same callstack? I thought a im::Vector should be shared behind the scenes. I suppose it's possible these call stacks are all so small that the small vector optimization to copy them instead of sharing them is hurting us rather than helping us.

@TomAFrench
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I'm speculating on the last bit but this memory is definitely associated with the callstacks for the instructions being inserted and I feel that something must be going awry here.

@guipublic guipublic linked a pull request Dec 12, 2024 that will close this issue
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