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Custom Memory Allocators (Pool, Arena, Stack) for High-Frequency Game Loops: Historical Paradigm Evolution and Next-Gen Architectural Projections

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  • #118122
    User AvatarOwen Nelson
    Member

    I’ve been rebuilding my game loop’s allocation strategy from the ground up and I’m curious how many of you have actually moved off the default heap for frame-critical paths. For years I was stuck on a simple bump allocator that worked fine until I started spawning pooled entities per frame—suddenly I was hitting cache thrashing on hot paths and the occasional fragmentation stall mid-match. So here’s what’s keeping me up: for a tightly-looped simulation with predictable object lifetimes, does a fixed-size pool allocator still beat a slab arena when you’re chasing zero-allocation frames, or have most of you gone straight to a stack-based free-list approach?

    Also, on the legacy front—how many of you are still maintaining old reference-counted allocators that I know are basically dead weight now? And more importantly, what’s your take on thread-local arenas for multi-core frame prediction? Are the synchronization headaches worth it, or are you relying on per-thread pools with periodic merges? I’ve read that monotonic arena patterns are making a comeback for next-gen engines, but I want real-world numbers from people actually shipping this in competitive titles, not benchmark theory. Have any of you tested arena allocators under sustained long-session play to see how they hold up against fragmentation over hours of runtime?

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    #119026

    Great topic to kick things off. The historical arc here is pretty clear if you look at how engine teams stopped fighting the allocator and started designing around allocation patterns instead. Early engines leaned on raw malloc/free and fixed heaps, which worked until games got bigger and frame-time variance from the system allocator started tanking competitive players’

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    #120633
    User AvatarLiam Vance
    Member

    Solid topic. The thing I keep seeing people get wrong is treating these three as interchangeable “fast allocators” when they’re really solving different lifetime problems. Pool allocators win for homogeneous, long-lived-ish entities—projectiles, particles,

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